Pith. sign in

Paper Citation Record · LEDGER

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems

As of 8 August 2026, this Paper Citation Record lists 74 of 74 outbound references and 0 inbound Pith citation observations for arXiv:2506.15719.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2506.15719 v1

Coverage vector

measured 74 of 74 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:10:46.054000Z

measured 74 of 74 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

74 of 74 outbound references displayed

  • verified exact0
  • verified fuzzy66
  • unresolved8
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 30a59c7b-1e72-4b80-acb8-43e82e0c1514 · outbound

This paper cites Heat pumps and our low-carbon future: A comprehensive review, Energy Research & Social Science 2021, 71, 101764.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems Heat pumps and our low-carbon future: A comprehensive review, Energy Research & Social Science 2021, 71, 101764

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:56.357348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.683313Z digest=sha256:f2407ce95dca3578d2dfb78821679033647ce20e5a072a5051326fd201a41216

Observation ed6cbee2-be64-4691-80f1-36de54e770a6 · outbound

This paper cites Energy flexible heat pumps in industrial energy systems: A review, Energy Reports 2023, 9, 386--394.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems Energy flexible heat pumps in industrial energy systems: A review, Energy Reports 2023, 9, 386--394

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:56.234885Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.689075Z digest=sha256:e8fea1cde451590b1a754cd99ffcec575be02bb30f3f9d85ec56f3176e23be35

Observation dbb757ed-fc74-40d7-911d-d8d6c1349a83 · outbound

This paper cites Machine Learning and Deep Learning in Energy Systems: A Review, Sustainability 2022, 14 (8).

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems Machine Learning and Deep Learning in Energy Systems: A Review, Sustainability 2022, 14 (8)

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:56.126830Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.694487Z digest=sha256:9339491a3ff4f73152e34a33e7d9372bfcf51aed1221596c5d9d1cd30e43245d

Observation a54cb4e0-01b8-46a5-a5ec-323f85cc3179 · outbound

This paper cites A review on renewable energy and electricity requirement forecasting models for smart grid and buildings, Sustainable Cities and Society 2020, 55, 102052.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems A review on renewable energy and electricity requirement forecasting models for smart grid and buildings, Sustainable Cities and Society 2020, 55, 102052

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:55.988882Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.700385Z digest=sha256:29ddc24f6499c4a7fc28a13e9b85d4aa91dcb711946ac8b563ae2cab0694aed4

Observation 68bc4b08-100a-4045-b1d9-4415ebdb2fbc · outbound

This paper cites Optimizing renewable energy systems through artificial intelligence: Review and future prospects, Energy & Environment 2024, 35 (7), 3833--3879.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems Optimizing renewable energy systems through artificial intelligence: Review and future prospects, Energy & Environment 2024, 35 (7), 3833--3879

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:55.847659Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.706025Z digest=sha256:dfa492392011a3cc4d2f3ba1ddeb0f2f7459682a5ebd77ed8d0e2b7b4c509df1

Observation b8c4c48f-e481-410f-90c8-7f2b265675f3 · outbound

This paper cites Heating up the global heat pump market, Nature Energy 2022, 7 (10), 901--904.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems Heating up the global heat pump market, Nature Energy 2022, 7 (10), 901--904

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:55.711067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.710710Z digest=sha256:0f737994fbb51b6927c5bec86c91899bf9bc59c9ae384e8de0d72e51e7706514

Observation 92818bb2-93a3-4dad-9a49-5997baf74b4e · outbound

This paper cites Estimating electric power consumption of in-situ residential heat pump systems: A data-driven approach, Applied Energy 2023, 352, 121971.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems Estimating electric power consumption of in-situ residential heat pump systems: A data-driven approach, Applied Energy 2023, 352, 121971

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:55.547537Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.716048Z digest=sha256:ea703d44b36db42c9a1532cc55f6f5c2f495692297e7d9c9f1d19a080a9a8dd6

Observation b9ab1ebc-94af-4949-9851-e2f047e8b342 · outbound

This paper cites Artificial intelligence and machine learning approaches to energy demand-side response: A systematic review, Renewable and Sustainable Energy Reviews 2020, 130, 109899.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems Artificial intelligence and machine learning approaches to energy demand-side response: A systematic review, Renewable and Sustainable Energy Reviews 2020, 130, 109899

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:55.407961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.720699Z digest=sha256:63c14ffa300451c5dd8870547674ae45837e9e21277a77bd08bfd7852a5f2357

Observation 79fbecbc-4382-4526-8289-9f9e693a1606 · outbound

This paper cites Data-driven soft sensors targeting heat pump systems, Energy Conversion and Management 2023, 279, 116769.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems Data-driven soft sensors targeting heat pump systems, Energy Conversion and Management 2023, 279, 116769

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:55.258826Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.725076Z digest=sha256:b7e31f26166d5585f1ffa3d4c6c9ec7853eef1ad78c9dca097fde7c4d35ea9f5

Observation b9dcea6d-2238-4f62-bf30-fc8c2f82628f · outbound

This paper cites Recent advances in the analysis of residential electricity consumption and applications of smart meter data, Applied Energy 2017, 208, 402--427.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems Recent advances in the analysis of residential electricity consumption and applications of smart meter data, Applied Energy 2017, 208, 402--427

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:55.126919Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.729623Z digest=sha256:f71ae0a7207c3cdae631641b4a40e5b42aa16f621de7ccd60638f8d2d8865b97

Observation 55754119-c807-4327-b3ef-26ad9fefc58f · outbound

This paper cites DA-LSTM: A dynamic drift-adaptive learning framework for interval load forecasting with LSTM networks, Engineering Applications of Artificial Intelligence 2023, 123, 106480.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems DA-LSTM: A dynamic drift-adaptive learning framework for interval load forecasting with LSTM networks, Engineering Applications of Artificial Intelligence 2023, 123, 106480

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:54.989400Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.734077Z digest=sha256:38bb7bef19ac209c0af7d892f3c6d044e222348a9486a20b05d7afe3f4b95490

Observation a4caec01-be95-4432-8c13-d5a1c7a09ff4 · outbound

This paper cites Deep Learning in Fault Detection and Diagnosis of building HVAC Systems: A Systematic Review with Meta Analysis, Energy and AI 2023, 12, 100235.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems Deep Learning in Fault Detection and Diagnosis of building HVAC Systems: A Systematic Review with Meta Analysis, Energy and AI 2023, 12, 100235

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:54.851845Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.738057Z digest=sha256:ff17bfa372d34a2fd5e11ea1a1793f5c0754c3ab942f94c1e6e14c947af80d9e

Observation 963e6d3d-0997-44c0-a7b8-a28453f8e21a · outbound

This paper cites A systematic review of machine learning techniques related to local energy communities, Renewable and Sustainable Energy Reviews 2022, 170, 112651.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems A systematic review of machine learning techniques related to local energy communities, Renewable and Sustainable Energy Reviews 2022, 170, 112651

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:54.686429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.744307Z digest=sha256:0ad87994ca54fda2814217c1505aa675ebd82b6f3e85683b10ba91d50113448b

Observation 8aae53cb-a236-4c2f-b7a9-a9f80d4991ba · outbound

This paper cites An application of the artificial neural network to optimise the energy performances of a magnetic refrigerator, International Journal of Refrigeration 2017, 82, 238--251.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems An application of the artificial neural network to optimise the energy performances of a magnetic refrigerator, International Journal of Refrigeration 2017, 82, 238--251

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:54.533924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.749784Z digest=sha256:1af149cd72013b921eb35046dc028448d61d2dec8fc665cd5cf7e88a09b19ad5

Observation e04b52ad-d659-4623-b04f-78874868be73 · outbound

This paper cites Artificial intelligence models for refrigeration, air conditioning and heat pump systems, Energy Reports 2022, 8, 8451--8466.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems Artificial intelligence models for refrigeration, air conditioning and heat pump systems, Energy Reports 2022, 8, 8451--8466

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:54.383771Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.754931Z digest=sha256:7ac24dca90ac7f21cf8e8f4717f412e82304b346346dcad73d075f1f3544dd99

Observation 2bb9d7ad-ef76-4338-a035-99eb89422625 · outbound

This paper cites A deep learning framework for building energy consumption forecast, Renewable and Sustainable Energy Reviews 2021, 137, 110591.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems A deep learning framework for building energy consumption forecast, Renewable and Sustainable Energy Reviews 2021, 137, 110591

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:54.231348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.759970Z digest=sha256:2f1d4911cf0136c2c0270fdc3c723eae1b0b999f1f93bf98a494cf2268e58f0c

Observation 7ff8ad48-1412-46fc-b514-5f528ea2f88c · outbound

This paper cites A review on machine learning forecasting growth trends and their real-time applications in different energy systems, Sustainable Cities and Society 2020, 54, 102010.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems A review on machine learning forecasting growth trends and their real-time applications in different energy systems, Sustainable Cities and Society 2020, 54, 102010

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:54.088619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.765271Z digest=sha256:cbd7033cd8de6c5bd47f5a27e0778288552a8771d7d0e45a7dc1fc549d136354

Observation ac070e63-4b9e-4c8e-9ca1-a3fa23e4bc53 · outbound

This paper cites Bayesian approach and time series dimensionality reduction to LSTM-based model-building for fault diagnosis of a reciprocating compressor, Neurocomputing 2020, 380, 51--66.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems Bayesian approach and time series dimensionality reduction to LSTM-based model-building for fault diagnosis of a reciprocating compressor, Neurocomputing 2020, 380, 51--66

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:53.949329Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.771373Z digest=sha256:7c5ddb740aaee5590d92ea98673f18fc3c7cb130c22fc547fb526d581d853e2e

Observation 077b40a9-ae6b-4db6-80da-1b14fa24987a · outbound

This paper cites An optimized model using LSTM network for demand forecasting, Computers & Industrial Engineering 2020, 143, 106435.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems An optimized model using LSTM network for demand forecasting, Computers & Industrial Engineering 2020, 143, 106435

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:53.692937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.776905Z digest=sha256:905f1dddf9ab561a748f355ca8bfb10a6f84b7c39b539bb002647c4881dad07e

Observation 6fdca115-22c1-4e38-ba96-2f6bb1da7266 · outbound

This paper cites Fault detection and diagnosis of large-scale HVAC systems in buildings using data-driven methods: A comprehensive review, Energy and Buildings 2020, 229, 110492.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems Fault detection and diagnosis of large-scale HVAC systems in buildings using data-driven methods: A comprehensive review, Energy and Buildings 2020, 229, 110492

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:53.428454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.782144Z digest=sha256:9a33f52ccd668dbb03022f27a12edae65b34ee8b26f444d25bc7dd7c7259b3b7

Observation cb76763b-701b-4ad0-81c3-80fe16288843 · outbound

This paper cites Large-scale heat pumps: Applications, performance, economic feasibility and industrial integration, Renewable and Sustainable Energy Reviews 2020, 133, 110219.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems Large-scale heat pumps: Applications, performance, economic feasibility and industrial integration, Renewable and Sustainable Energy Reviews 2020, 133, 110219

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:53.121057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.787942Z digest=sha256:ad0a521473b4aa409fcfba322063119446e2279843fcc10d892db2b86412f00a

Observation 21b99978-edcd-4945-a999-ce7a7eefb921 · outbound

This paper cites A long short-term memory artificial neural network to predict daily HVAC consumption in buildings, Energy and Buildings 2020, 216, 109952.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems A long short-term memory artificial neural network to predict daily HVAC consumption in buildings, Energy and Buildings 2020, 216, 109952

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:52.869673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.793449Z digest=sha256:a430dc9ced6362ab0db40f738b7763b494b62f14d3bc1374308628f0ced82055

Observation 812818bc-3d41-40a0-ad8d-6c0435c06151 · outbound

This paper cites Short-term electricity consumption forecast with artificial neural networks—A case study of office buildings, In 2017 IEEE Manchester PowerTech, IEEE, 2017; pp 1--6.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems Short-term electricity consumption forecast with artificial neural networks—A case study of office buildings, In 2017 IEEE Manchester PowerTech, IEEE, 2017; pp 1--6

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:52.546369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.798242Z digest=sha256:93ade5a05cb4e22b91bec2926828c4c8595837497205cfef1afe9e88738e6276

Observation 7cd50e56-6054-4d0a-949c-4cba177dca33 · outbound

This paper cites Using long short-term memory networks to predict energy consumption of air-conditioning systems, Sustainable Cities and Society 2020, 55, 102000.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems Using long short-term memory networks to predict energy consumption of air-conditioning systems, Sustainable Cities and Society 2020, 55, 102000

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:52.251181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.803075Z digest=sha256:d050937efb69c64d168658ccc68e7cd7a330e940180587ccec31fc77c1b2265d

Observation 2d2e6585-75ef-48b1-8cf9-64c498b375ab · outbound

This paper cites A hybrid model approach for forecasting future residential electricity consumption, Energy and Buildings 2016, 117, 341--351.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems A hybrid model approach for forecasting future residential electricity consumption, Energy and Buildings 2016, 117, 341--351

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:51.974877Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.807515Z digest=sha256:20c2e4e88020a89a15c9651e1ab4c12375ec6014d1066f1965e78b0d9bfb1825

Observation d7aa16da-a7ad-4c8b-a6ca-8df52e055075 · outbound

This paper cites an unresolved cited work.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems Unresolved cited work

Reference 26

Resolution
unresolved
raw_fallback, observed 2026-08-07T11:10:51.792361Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.812766Z digest=sha256:47732bcf5ed42e924daaa573caef15c7d8a7de7f0ed41640672754cdca690f90

Observation c78b65dd-7f9e-47c1-8616-087dcd14701e · outbound

This paper cites Short-term residential load forecasting based on LSTM recurrent neural network, IEEE transactions on smart grid 2017, 10 (1), 841--851.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems Short-term residential load forecasting based on LSTM recurrent neural network, IEEE transactions on smart grid 2017, 10 (1), 841--851

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:51.590787Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.817893Z digest=sha256:1cc8bef1d22e93569cf18fafa61260886dcd97b1252ef77e8072d7760a64dc5c

Observation eeb761a6-32d8-4b06-ba62-c49d90768783 · outbound

This paper cites Building thermal load prediction through shallow machine learning and deep learning, Applied Energy 2020, 263, 114683.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems Building thermal load prediction through shallow machine learning and deep learning, Applied Energy 2020, 263, 114683

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:51.404877Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.822296Z digest=sha256:f397acf27aea39feb0f285ab558e4a28743823b6c65dab209e5e63a118fd195d

Observation a7dd3393-a400-40bd-afd2-0a3ecb8020ea · outbound

This paper cites A novel energy demand prediction strategy for residential buildings based on ensemble learning, Energy Procedia 2019, 158, 3411--3416.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems A novel energy demand prediction strategy for residential buildings based on ensemble learning, Energy Procedia 2019, 158, 3411--3416

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:51.190756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.827212Z digest=sha256:7579f7858c499c0a035262611fb501987e1beeb3508b619509bbd19f9d957da0

Observation b582b276-4b11-482f-888f-170184105dff · outbound

This paper cites Oil and gold price prediction using optimized fuzzy inference system based extreme learning machine, Resources Policy 2022, 79, 103109.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems Oil and gold price prediction using optimized fuzzy inference system based extreme learning machine, Resources Policy 2022, 79, 103109

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:51.006739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.831970Z digest=sha256:222efe9fbcd1e3d9f80c562ff1216cab6403b01a704ae165ea75bc64a2fedc77

Observation 1eb09006-34b5-455b-b08b-14d505ed8ac2 · outbound

This paper cites an unresolved cited work.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems Unresolved cited work

Reference 31

Resolution
unresolved
raw_fallback, observed 2026-08-07T11:10:50.822481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.837307Z digest=sha256:eb4f75bbaaae6aa44d2f950b5f3d92598b68c58e504a53c21925c17b88593383

Observation bcfb8a4b-5e04-4022-8d54-282e111c2130 · outbound

This paper cites an unresolved cited work.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems Unresolved cited work

Reference 32

Resolution
unresolved
raw_fallback, observed 2026-08-07T11:10:50.567979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.842164Z digest=sha256:f1c72029a4238cfd76839b72450cd4398dd4af2e1fe0c798fae3026aeff348bf

Observation 38b45090-2e34-4020-b26e-bc5a4e3acd99 · outbound

This paper cites Revolutionizing Sustainable Energy Production with Quantum Artificial Intelligence: Applications in Autonomous Robotics and Data Management, Green and Low-Carbon Economy 2023.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems Revolutionizing Sustainable Energy Production with Quantum Artificial Intelligence: Applications in Autonomous Robotics and Data Management, Green and Low-Carbon Economy 2023

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:50.344641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.846933Z digest=sha256:29c221b08a24b879656306038a20b3ff99f4b0d482000d67cf341ace83e4de0a

Observation 4c8797e0-e8db-4749-8ae7-d3cb58e9fdcf · outbound

This paper cites A Semi-Supervised Modulation Identification in MIMO Systems: A Deep Learning Strategy, IEEE Access 2022, 10, 76622--76635.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems A Semi-Supervised Modulation Identification in MIMO Systems: A Deep Learning Strategy, IEEE Access 2022, 10, 76622--76635

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:50.193518Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.852358Z digest=sha256:a914b5b3552b32957e69ee98028f26e56861af10213e50b211119deb80b56264

Observation 906c68da-6c76-44da-82e5-877705bea8b1 · outbound

This paper cites Automatic fault detection in grid-connected photovoltaic systems via variational autoencoder-based monitoring, Energy Conversion and Management 2024, 314, 118665.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems Automatic fault detection in grid-connected photovoltaic systems via variational autoencoder-based monitoring, Energy Conversion and Management 2024, 314, 118665

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:50.013851Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.857019Z digest=sha256:9756a09278f1a9d9a50f973aff894a0844b27af67d058fce786e80e7defe3ffb

Observation 4bed40f3-f3cd-4e6c-abf2-1f43aed7bca3 · outbound

This paper cites TransNAS-TSAD: Harnessing Transformers for Multi-Objective Neural Architecture Search in Time Series Anomaly Detection, Neural Computing & Applications 2024.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems TransNAS-TSAD: Harnessing Transformers for Multi-Objective Neural Architecture Search in Time Series Anomaly Detection, Neural Computing & Applications 2024

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:49.761867Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.861285Z digest=sha256:9afa62044ea69f384c2fbc25bdeb7682d8ed4214d4c54c13f8726233baef2243

Observation 4d044258-acdd-4e3c-a333-b97bc1e22337 · outbound

This paper cites Peak Anomaly Detection from Environmental Sensor-Generated Watershed Time Series Data, In Information Management and Big Data.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems Peak Anomaly Detection from Environmental Sensor-Generated Watershed Time Series Data, In Information Management and Big Data

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:49.577678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.866703Z digest=sha256:037740c04de160f3724712b7f8b2748963a7e370457c3e30b2f21130c21c5608

Observation db9fce45-cd67-4352-8cee-74dec5dfc00b · outbound

This paper cites General review of ground-source heat pump systems for heating and cooling of buildings, Energy and Buildings 2014, 70, 441--454.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems General review of ground-source heat pump systems for heating and cooling of buildings, Energy and Buildings 2014, 70, 441--454

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:49.354837Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.871793Z digest=sha256:91f509971c480fa635ecbabcbdce04d3a1ccb0a266327469b3ba4542cced95d1

Observation c224b0a1-677d-4a3d-bb84-3649b062d8f2 · outbound

This paper cites Machine learning-based performance prediction for ground source heat pump systems, Geothermics 2022, 105, 102509.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems Machine learning-based performance prediction for ground source heat pump systems, Geothermics 2022, 105, 102509

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:49.133785Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.877323Z digest=sha256:5a9f17c412789c746e8f44f935ae73071dbce0ccdcc650cb10007a43eb462d71

Observation 96c56ac8-1898-4592-8993-e67f988848ee · outbound

This paper cites an unresolved cited work.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems Unresolved cited work

Reference 40

Resolution
unresolved
raw_fallback, observed 2026-08-07T11:10:48.953599Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.881832Z digest=sha256:48e3e2ca15cf8ab35f41e78f2c9c853e111029eb540e5110523431beb27c92f4

Observation 45beb062-f3f9-4cbe-b266-ed9c6269c40b · outbound

This paper cites RNN-LSTM: From applications to modeling techniques and beyond—Systematic review, Journal of King Saud University - Computer and Information Sciences 2024, 36 (5), 102068.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems RNN-LSTM: From applications to modeling techniques and beyond—Systematic review, Journal of King Saud University - Computer and Information Sciences 2024, 36 (5), 102068

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:48.773806Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.886606Z digest=sha256:568be1465279d25e0130aebb67048ec3e06c113432c21684e463059042437681

Observation cfac3fa6-e819-4b0f-8a03-746046cd168a · outbound

This paper cites A Lightweight Concept Drift Detection and Adaptation Framework for IoT Data Streams, IEEE Internet of Things Magazine 2021, 4 (2), 96--101.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems A Lightweight Concept Drift Detection and Adaptation Framework for IoT Data Streams, IEEE Internet of Things Magazine 2021, 4 (2), 96--101

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:48.554814Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.891106Z digest=sha256:60e46cdd19eebb561415779edde459d40424cce6717d6bb6ea484de1df24d820

Observation be804156-90dd-433a-87ca-51cedfdc4f00 · outbound

This paper cites Light gradient boosting machine with optimized hyperparameters for identification of malicious access in IoT network, Digital Communications and Networks 2023, 9 (1), 125--137.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems Light gradient boosting machine with optimized hyperparameters for identification of malicious access in IoT network, Digital Communications and Networks 2023, 9 (1), 125--137

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:48.353516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.895900Z digest=sha256:1d0599afaf369d37b8b48cfa7be4746fa95d3e9429be20a59752b19dd83338a9

Observation 849a3b3c-4078-456e-a89b-cdb56d2d3c8d · outbound

This paper cites Intrusion detection model of Internet of Things based on LightGBM, IEICE Transactions on Communications 2023, 106 (8), 622--634.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems Intrusion detection model of Internet of Things based on LightGBM, IEICE Transactions on Communications 2023, 106 (8), 622--634

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:48.194959Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.900797Z digest=sha256:e14e73ff33670cf6d4a936fe936330e915c0b2cf7b7174c5f984f7a29cf17d3a

Observation 4a1474e2-2327-4e1c-bc8b-a468391788ec · outbound

This paper cites Multi-sensor Data Fusion Method Based on ARIMA-LightGBM for AGV Positioning, In 2021 5th International Conference on Robotics and Automation Sciences (ICRAS), 2021; pp 272--276.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems Multi-sensor Data Fusion Method Based on ARIMA-LightGBM for AGV Positioning, In 2021 5th International Conference on Robotics and Automation Sciences (ICRAS), 2021; pp 272--276

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:47.993472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.905792Z digest=sha256:8c4a669b17f1d2813a360fda368eebd4b27cc080e044e3eb5531f5944a327756

Observation 1e049bb6-c27b-4667-bc53-bbbee5ddb821 · outbound

This paper cites an unresolved cited work.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems Unresolved cited work

Reference 46

Resolution
unresolved
raw_fallback, observed 2026-08-07T11:10:47.829150Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.910294Z digest=sha256:010c11e89534d28b41516b4742cf7072d1d788709d27b126127461ec839d0674

Observation eba29edb-77cb-4a32-9c7b-862a63183714 · outbound

This paper cites Long short-term memory, Neural computation 1997, 9 (8), 1735--1780.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems Long short-term memory, Neural computation 1997, 9 (8), 1735--1780

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:47.679524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.915018Z digest=sha256:7fd67129a6df352f718074780e4ea9e0ee82486cb71dbdcb30a038c44478f3ce

Observation ddcead68-af0a-49da-851f-d51f02c187dc · outbound

This paper cites A review of data-driven approaches for prediction and classification of building energy consumption, Renewable and Sustainable Energy Reviews 2018, 82, 1027--1047.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems A review of data-driven approaches for prediction and classification of building energy consumption, Renewable and Sustainable Energy Reviews 2018, 82, 1027--1047

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:47.518769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.920000Z digest=sha256:42c60a4c88eef28b21e7579ee6b38c2b2931b5726bcc8accb5acd47cee5299bd

Observation 99b379fb-a99e-4f46-9d2f-8cbe5d0b34e2 · outbound

This paper cites A comparative performance analysis of different activation functions in LSTM networks for classification, Neural Computing and Applications 2019, 31, 2507--2521.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems A comparative performance analysis of different activation functions in LSTM networks for classification, Neural Computing and Applications 2019, 31, 2507--2521

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:47.316675Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.925600Z digest=sha256:676554c1e91b117364f7522e61abacf975c07be7886e8e9e529475d876b1044f

Observation 77bf5cb2-6498-47fe-b810-161a8eaeb49c · outbound

This paper cites LSTM inefficiency in long-term dependencies regression problems, Journal of Advanced Research in Applied Sciences and Engineering Technology 2023, 30 (3), 16--31.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems LSTM inefficiency in long-term dependencies regression problems, Journal of Advanced Research in Applied Sciences and Engineering Technology 2023, 30 (3), 16--31

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:47.127360Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.930680Z digest=sha256:788c3f4f9bcc4f5c2948cce90ff265703c58c67954d6b9362089e9ea9512607a

Observation c8bd1e0e-0d5b-44c3-a39b-f1792d1e3fbd · outbound

This paper cites A survey on anomaly detection for technical systems using LSTM networks, Computers in Industry 2021, 131, 103498.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems A survey on anomaly detection for technical systems using LSTM networks, Computers in Industry 2021, 131, 103498

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:46.959937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.936409Z digest=sha256:70871bbf9138a13d876562dd796f85d0b2abd78881c391ea8821a8f279352ead

Observation 2cfc3128-f8a6-45d2-9646-16babb88656a · outbound

This paper cites A novel attLSTM framework combining the attention mechanism and bidirectional LSTM for demand forecasting, Expert Systems with Applications 2024, 254, 124409.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems A novel attLSTM framework combining the attention mechanism and bidirectional LSTM for demand forecasting, Expert Systems with Applications 2024, 254, 124409

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:46.790686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.940863Z digest=sha256:c18f86455f97d667690c4053786b1fa63df3194c4bdea07807e092a80537629a

Observation 85db2c3e-1248-4530-8f30-e6a4f451fb96 · outbound

This paper cites Paraphrase detection using LSTM networks and handcrafted features, Multimedia Tools and Applications 2021, 80 (4), 6479--6492.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems Paraphrase detection using LSTM networks and handcrafted features, Multimedia Tools and Applications 2021, 80 (4), 6479--6492

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:46.636862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.945588Z digest=sha256:2b2bda79c5e808163f1fbf5fc6042d0dac7829e6ef2da4624fb80852517c7a7c

Observation 893b0a34-3f93-4aa3-8e03-cdbbc3c6cb52 · outbound

This paper cites an unresolved cited work.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems Unresolved cited work

Reference 54

Resolution
unresolved
raw_fallback, observed 2026-08-07T11:10:46.547193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.950530Z digest=sha256:b26454973fbcd1a87f5c2b3c064bd88f5059d3f8b26faece627535cd17f9f104

Observation cd0da095-f4d6-4428-9c87-243dd3d2902d · outbound

This paper cites an unresolved cited work.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems Unresolved cited work

Reference 55

Resolution
unresolved
raw_fallback, observed 2026-08-07T11:10:46.522204Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.954757Z digest=sha256:8ca0a8e3bdb25010472bdd1a2d26ab24ecb027ee5dd2f06ca1ccf6e529ac535c

Observation 0be5da88-0b23-46b8-904b-29d684e8d266 · outbound

This paper cites Unidirectional and bidirectional LSTM models for short-term traffic prediction, Journal of Advanced Transportation 2021, 2021 (1), 5589075.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems Unidirectional and bidirectional LSTM models for short-term traffic prediction, Journal of Advanced Transportation 2021, 2021 (1), 5589075

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:46.497161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.959106Z digest=sha256:94836296685ddd3981b63e3b0d6723c82062aa62e6a07efdf3e5269ed2723d7d

Observation 3e2778a5-a796-44eb-91c8-17fe50b830cc · outbound

This paper cites Extended Isolation Forest, IEEE Transactions on Knowledge and Data Engineering 2021, 33 (4), 1479--1489.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems Extended Isolation Forest, IEEE Transactions on Knowledge and Data Engineering 2021, 33 (4), 1479--1489

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:46.443273Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.965229Z digest=sha256:9e5cfda756f77de25a91c81bd459b8ce641104270ebc8d81053e4e7e4312f580

Observation ebc3fad4-ba28-4033-b897-6184b136257c · outbound

This paper cites Anomaly detection: A survey, ACM Comput.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems Anomaly detection: A survey, ACM Comput

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:46.402118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.970458Z digest=sha256:8bf2c0bd6fc2132feb961c092d3035e1b6ade9fb14b3970669476d3a891f6879

Observation a84c70ca-3211-4a2a-a88f-40074bf3df1b · outbound

This paper cites New Trends in Time Series Anomaly Detection., In EDBT, 2023; pp 847--850.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems New Trends in Time Series Anomaly Detection., In EDBT, 2023; pp 847--850

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:46.373270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.975042Z digest=sha256:68a52caf63b209ead6c1294be3084f25b53947bcc52d51479e3075042bc35fca

Observation b2b38be0-fd41-46df-a47b-29780e123a51 · outbound

This paper cites An In-Depth Study and Improvement of Isolation Forest, IEEE Access 2022, 10, 10219--10237.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems An In-Depth Study and Improvement of Isolation Forest, IEEE Access 2022, 10, 10219--10237

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:46.357252Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.980773Z digest=sha256:7defc584022c7149fc745ebec7a017710e30a53d77de40dc3177c84ce002ca38

Observation 087727f8-e50a-4a0d-a0b4-ced7ab219a59 · outbound

This paper cites l-DBSCAN : A Fast Hybrid Density Based Clustering Method, In 18th International Conference on Pattern Recognition (ICPR'06), 2006; Vol.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems l-DBSCAN : A Fast Hybrid Density Based Clustering Method, In 18th International Conference on Pattern Recognition (ICPR'06), 2006; Vol

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:46.341241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.986936Z digest=sha256:46f44eb5ecc7df99773ab8619da181ea423ffe9393454aa6f6e3c8891818e87f

Observation e98bd904-d7cd-40c7-b62f-a601a670ebe7 · outbound

This paper cites Approximate training of one-class support vector machines using expected margin, Computers & Industrial Engineering 2019, 130, 772--778.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems Approximate training of one-class support vector machines using expected margin, Computers & Industrial Engineering 2019, 130, 772--778

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:46.324782Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.991596Z digest=sha256:ea10a98314774adc665fb0629c09caf4d19f3c9457f3ebb05724906c7dcd2f9a

Observation 8b61c6a1-e24c-4135-b4dc-57edf1588f3f · outbound

This paper cites Autoencoders and their applications in machine learning: a survey, Artificial Intelligence Review 2024, 57 (2), 28.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems Autoencoders and their applications in machine learning: a survey, Artificial Intelligence Review 2024, 57 (2), 28

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:46.309522Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:45.997197Z digest=sha256:78249f1bb8612eccc29b796f24121d92b48ca40e95ea3d09379cb807863966b4

Observation c085f268-4418-4a8d-a990-fe447b127bb8 · outbound

This paper cites Isolation forest, In 2008 eighth ieee international conference on data mining, IEEE, 2008; pp 413--422.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems Isolation forest, In 2008 eighth ieee international conference on data mining, IEEE, 2008; pp 413--422

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:46.291306Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:46.002330Z digest=sha256:5a8d114cf419720a417450c1b3d2743972c672e90933544c694064cf51b2b9b3

Observation 1be78495-739b-49b6-a7c5-2f96b20e3206 · outbound

This paper cites an unresolved cited work.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems Unresolved cited work

Reference 65

Resolution
unresolved
raw_fallback, observed 2026-08-07T11:10:46.274855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:46.007932Z digest=sha256:039300c7d940a282ff610e0a7c35627ee8858eec28df725449c1eab02ee1c89e

Observation 48271419-ab0f-464f-8ccc-4d48bc20f80b · outbound

This paper cites Effects of data preprocessing on detecting autism in adults using web-based eye-tracking data, Behaviour & Information Technology 2023, 42 (14), 2476--2484.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems Effects of data preprocessing on detecting autism in adults using web-based eye-tracking data, Behaviour & Information Technology 2023, 42 (14), 2476--2484

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:46.257323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:46.013563Z digest=sha256:b8b0a7c82d1664f3f5cd733cc97401a9c7269b953cd0a180b878b27fde93ffac

Observation f1a1ec4e-5f44-462b-b196-edbdc0f6c6b2 · outbound

This paper cites Missing data in time series: A review of imputation methods and case study, Learning and Nonlinear Models 2022, 20 (1), 31--46.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems Missing data in time series: A review of imputation methods and case study, Learning and Nonlinear Models 2022, 20 (1), 31--46

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:46.240450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:46.018383Z digest=sha256:f11b34c644b8eee9a4f2977868e901a0614670fa01d6352e06839f554ea3aacc

Observation 23bb35f2-a760-4a97-996c-f1ecc1a3a537 · outbound

This paper cites v‐plots: Designing Hybrid Charts for the Comparative Analysis of Data Distributions, Computer Graphics Forum 2020, 39, 565--577.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems v‐plots: Designing Hybrid Charts for the Comparative Analysis of Data Distributions, Computer Graphics Forum 2020, 39, 565--577

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:46.224245Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:46.022931Z digest=sha256:91913a8781383b0a920a286124a4519d0ad5db59b33dc0fe4190d00a01ae51f5

Observation 88faa181-3d64-4092-9f24-5d577945675a · outbound

This paper cites Random feature selection using random subspace logistic regression, Expert Systems with Applications 2023, 217, 119535.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems Random feature selection using random subspace logistic regression, Expert Systems with Applications 2023, 217, 119535

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:46.206819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:46.029490Z digest=sha256:5457658a1d5d13b6dea16bf2f2d04db18c65bf37711e76a4bdccec7781facb23

Observation 87effed6-f326-4dae-8b90-f90d8c2a840f · outbound

This paper cites Anomaly detection based on machine learning in IoT-based vertical plant wall for indoor climate control, Building and Environment 2020, 183, 107212.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems Anomaly detection based on machine learning in IoT-based vertical plant wall for indoor climate control, Building and Environment 2020, 183, 107212

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:46.187846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:46.034540Z digest=sha256:5a91f367df68a5c68dff7b9c0c9d17964d84c041f686bcd14e1e687df03491be

Observation 4dae4e34-427e-4429-aa59-c4b644bdce32 · outbound

This paper cites Electricity load forecasting: a systematic review, Journal of Electrical Systems and Information Technology 2020, 7, 1--19.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems Electricity load forecasting: a systematic review, Journal of Electrical Systems and Information Technology 2020, 7, 1--19

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:46.156878Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:46.039214Z digest=sha256:40457ed7c1fa363ec8d39991299dc14f1f7becf7d2142b5be75a5d5cd99ac298

Observation 08d989c7-710c-4119-9698-a24187dc5387 · outbound

This paper cites Global vs.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems Global vs

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:46.140393Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:46.043978Z digest=sha256:cea9ece326c61ea0d1b801c2c7fb50d072466c12e35744c72deb0da54bcbcc52

Observation 7e607084-efcd-45f7-b5c7-fe644dda6e58 · outbound

This paper cites , " * write output.state after.block =.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems , " * write output.state after.block =

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:46.124294Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:46.048545Z digest=sha256:250506eaec9ef8803ae1e921c7186e2ac2bb4f91a3ffe37f80f604ac581f14bf

Observation 5253b47b-ba2c-47ef-8c7c-88db7d8a9ced · outbound

This paper cites write newline.

Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems write newline

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T11:10:46.107091Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T11:10:46.054000Z digest=sha256:71df42de806068c59e14ee1b4b9367028cd992f44df43af91be0320d1f8a6fbc

Pith citing papers

No inbound Pith citation observations are available.