Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning | Paper Citation Record

Observation 43a23cc4-97c5-4041-ac82-6ed53c1669b4 · outbound

This paper cites Securing water as a resource for society: An ecosystem services perspective,.

Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning Securing water as a resource for society: An ecosystem services perspective,

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This paper cites Progress in understanding harmful algal blooms: Paradigm shifts and new tech- nologies for research, monitoring, and management,.

Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning Progress in understanding harmful algal blooms: Paradigm shifts and new tech- nologies for research, monitoring, and management,

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This paper cites Cyanobacterial harmful algal blooms in aquatic ecosystems: A comprehensive outlook on current and emerging mitigation and control approaches,.

Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning Cyanobacterial harmful algal blooms in aquatic ecosystems: A comprehensive outlook on current and emerging mitigation and control approaches,

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This paper cites Increasingly severe cyanobacterial blooms and deep water hypoxia coincide with warming water temperatures in reservoirs,.

Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning Increasingly severe cyanobacterial blooms and deep water hypoxia coincide with warming water temperatures in reservoirs,

Reference 4

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This paper cites Trophic state assessment of global inland waters using a MODIS-derived Forel-Ule index,.

Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning Trophic state assessment of global inland waters using a MODIS-derived Forel-Ule index,

Reference 5

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This paper cites The human factor: Weather bias in manual lake water quality monitoring,.

Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning The human factor: Weather bias in manual lake water quality monitoring,

Reference 6

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This paper cites Secchi disk depth estimation from water quality parame- ters: Artificial neural network versus multiple linear regression models?.

Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning Secchi disk depth estimation from water quality parame- ters: Artificial neural network versus multiple linear regression models?

Reference 7

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This paper cites Improving remote sensing estimation of Secchi disk depth for global lakes and reservoirs using machine learning methods,.

Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning Improving remote sensing estimation of Secchi disk depth for global lakes and reservoirs using machine learning methods,

Reference 8

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This paper cites A remote sensing and machine learning-based approach to forecast the onset of harmful algal bloom,.

Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning A remote sensing and machine learning-based approach to forecast the onset of harmful algal bloom,

Reference 9

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Observation b96117ae-b993-4fa8-a3d6-179950af5dfd · outbound

This paper cites Remote sensing for regional lake water quality assessment: Capabilities and limitations of current and upcoming satellite systems,.

Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning Remote sensing for regional lake water quality assessment: Capabilities and limitations of current and upcoming satellite systems,

Reference 10

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Observation 7df3ae4e-ff55-4d82-a033-ea5047104d00 · outbound

This paper cites Monitoring inland water quality using remote sensing: potential and limitations of spectral indices, bio-optical simulations, machine learning, and cloud computing,.

Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning Monitoring inland water quality using remote sensing: potential and limitations of spectral indices, bio-optical simulations, machine learning, and cloud computing,

Reference 11

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This paper cites Remote sensing of inland waters: Challenges, progress and future directions,.

Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning Remote sensing of inland waters: Challenges, progress and future directions,

Reference 12

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Observation 4106b20a-38a1-4a28-b9b8-7df40f4a08d7 · outbound

This paper cites Lagos-us landsat: Remotely sensed water quality estimates for u.s. lakes over 4 ha from 1984 to 2020,.

Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning Lagos-us landsat: Remotely sensed water quality estimates for u.s. lakes over 4 ha from 1984 to 2020,

Reference 13

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This paper cites Machine learning approach for water quality predictions based on multispectral satellite imageries,.

Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning Machine learning approach for water quality predictions based on multispectral satellite imageries,

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Observation 9693545a-46f2-4e74-8bef-c19396e60bc6 · outbound

This paper cites Prediction of algal chlorophyll-a and water clarity in monsoon-region reservoir using machine learning approaches,.

Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning Prediction of algal chlorophyll-a and water clarity in monsoon-region reservoir using machine learning approaches,

Reference 15

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This paper cites Forecasting water quality index in groundwater using artificial neural network,.

Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning Forecasting water quality index in groundwater using artificial neural network,

Reference 16

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Observation 937c82d0-80e8-42fa-bf82-49537e90be49 · outbound

This paper cites Water-quality data imputation with a high percentage of missing values: A machine learning approach,.

Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning Water-quality data imputation with a high percentage of missing values: A machine learning approach,

Reference 17

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Observation a74303e2-f99e-4891-ab4c-66df8ea56c89 · outbound

This paper cites Review of automated time series forecasting pipelines,.

Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning Review of automated time series forecasting pipelines,

Reference 18

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Observation 19abc944-e82f-49fe-a90b-e026ebc34d2f · outbound

This paper cites Effect of missing data on performance of learning algorithms for hydrologic predictions: Implications to an imputation technique,.

Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning Effect of missing data on performance of learning algorithms for hydrologic predictions: Implications to an imputation technique,

Reference 19

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Observation 2a4e99e0-87c9-43c6-9ee3-c75d511d19da · outbound

This paper cites Missing data and multiple imputation in clinical epidemiological research,.

Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning Missing data and multiple imputation in clinical epidemiological research,

Reference 20

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Observation eddbcf5e-6722-4686-a4e1-423ee4125e5c · outbound

This paper cites Recent progress on surface water quality models utilizing machine learning techniques,.

Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning Recent progress on surface water quality models utilizing machine learning techniques,

Reference 21

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Observation ded107c4-183e-4ca4-a02e-171492e20a13 · outbound

This paper cites Improving remote sensing estimation of secchi disk depth for global lakes and reservoirs using machine learning methods,.

Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning Improving remote sensing estimation of secchi disk depth for global lakes and reservoirs using machine learning methods,

Reference 22

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Observation 37fb1d55-122a-40fe-9fc9-fd45f8085a7a · outbound

This paper cites Lagos-us landsat: Remotely sensed water quality estimates for u.s. lakes over 4 ha from 1984 to 2020,.

Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning Lagos-us landsat: Remotely sensed water quality estimates for u.s. lakes over 4 ha from 1984 to 2020,

Reference 23

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Observation 89acc940-c939-492e-bc84-392f4539124b · outbound

This paper cites Remote sensing of lake water clarity: Performance and transferability of both historical algorithms and machine learning,.

Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning Remote sensing of lake water clarity: Performance and transferability of both historical algorithms and machine learning,

Reference 24

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Observation ce0565f9-566e-4689-aa26-5efbccc75105 · outbound

This paper cites Deep learning- based remote sensing retrieval of inland water quality: A review,.

Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning Deep learning- based remote sensing retrieval of inland water quality: A review,

Reference 25

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This paper cites Feature-driven hybrid attention learning for accurate water quality prediction,.

Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning Feature-driven hybrid attention learning for accurate water quality prediction,

Reference 26

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This paper cites Deep representation learning enables cross-basin water quality predic- tion under data-scarce conditions,.

Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning Deep representation learning enables cross-basin water quality predic- tion under data-scarce conditions,

Reference 27

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Observation 1169eb10-cc50-4e4d-a003-db6862751999 · outbound

This paper cites Sample size determination for prediction models via learning-type curves,.

Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning Sample size determination for prediction models via learning-type curves,

Reference 28

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This paper cites Missing data is poorly handled and reported in prediction model studies using machine learning: a literature review,.

Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning Missing data is poorly handled and reported in prediction model studies using machine learning: a literature review,

Reference 29

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This paper cites Missing data imputation of high-resolution temporal climate time series data,.

Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning Missing data imputation of high-resolution temporal climate time series data,

Reference 30

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Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning Maximum likelihood from incomplete data via the em algorithm,

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This paper cites Multiple imputation for nonresponse in surveys. new york, ny: Johnwiley & sons,.

Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning Multiple imputation for nonresponse in surveys. new york, ny: Johnwiley & sons,

Reference 32

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This paper cites Recurrent neural networks for multivariate time series with missing values,.

Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning Recurrent neural networks for multivariate time series with missing values,

Reference 33

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Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning Long-term missing value imputation for time series data using deep neural networks,

Reference 34

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Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning mice: Multivariate impu- tation by chained equations in r,

Reference 35

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This paper cites Missforest—non-parametric missing value imputation for mixed-type data,.

Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning Missforest—non-parametric missing value imputation for mixed-type data,

Reference 36

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Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning Missing data imputa- tion using optimal transport,

Reference 37

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Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning The midas touch: Accurate and scalable missing-data imputation with deep learning,

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Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning Miwae: Deep generative modelling and imputation of incomplete data sets,

Reference 39

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Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning Miracle: Causally-aware imputation via learning missing data mechanisms,

Reference 40

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Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning Gain: Missing data imputation using generative adversarial nets,

Reference 41

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This paper cites Imputation of missing streamflow data at multiple gauging stations in Benin Republic,.

Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning Imputation of missing streamflow data at multiple gauging stations in Benin Republic,

Reference 42

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This paper cites Multiple data imputation methods advance risk analysis and treatability of co-occurring inorganic chemicals in groundwater,.

Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning Multiple data imputation methods advance risk analysis and treatability of co-occurring inorganic chemicals in groundwater,

Reference 43

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This paper cites Multiple imputations by chained equations for recovering miss- ing daily streamflow observations: A case study of Langat River Basin in Malaysia,.

Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning Multiple imputations by chained equations for recovering miss- ing daily streamflow observations: A case study of Langat River Basin in Malaysia,

Reference 44

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This paper cites Out-of-sample tests of forecasting accuracy: An analysis and review,.

Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning Out-of-sample tests of forecasting accuracy: An analysis and review,

Reference 45

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This paper cites Projecting stream water quality using weighted regression on time, discharge, and season (wrtds): An example with drought conditions in the delaware river basin,.

Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning Projecting stream water quality using weighted regression on time, discharge, and season (wrtds): An example with drought conditions in the delaware river basin,

Reference 46

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This paper cites ProbTS: Benchmarking Point and Distributional Forecasting across Diverse Prediction Horizons.

Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning ProbTS: Benchmarking Point and Distributional Forecasting across Diverse Prediction Horizons

Reference 47

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Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning Adaptive machine learning for forecasting in wind energy: A dynamic, multi-algorithmic approach for short and long-term predictions,

Reference 48

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This paper cites The coefficient of determination r-squared is more informative than smape, mae, mape, mse and rmse in regression analysis evaluation,.

Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning The coefficient of determination r-squared is more informative than smape, mae, mape, mse and rmse in regression analysis evaluation,

Reference 49

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Observation 9b4d1aae-001e-4a17-a56c-7c8ad0427e76 · outbound

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Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning Recommending training set sizes for classification,

Reference 50

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Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning The learning-curve sam- pling method applied to model-based clustering,

Reference 51

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Observation dfe2049d-d9f0-4e41-a15d-d6f40d1ae331 · outbound

This paper cites How much complexity is war- ranted in a rainfall-runoff model?.

Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning How much complexity is war- ranted in a rainfall-runoff model?

Reference 52

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Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning Automatic time series forecasting: Theforecastpackage for r,

Reference 53

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Observation e37ef09c-447e-473f-ab99-a7f94e44e2e2 · outbound

This paper cites Analysis of the effectiveness of ARIMA, SARIMA, and SVR models in time series forecasting: A case study of wind farm energy production,.

Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning Analysis of the effectiveness of ARIMA, SARIMA, and SVR models in time series forecasting: A case study of wind farm energy production,

Reference 54

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This paper cites Statsmodels: Econometric and statistical modeling with python,.

Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning Statsmodels: Econometric and statistical modeling with python,

Reference 55

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This paper cites Darts: User-friendly modern machine learning for time series,.

Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning Darts: User-friendly modern machine learning for time series,

Reference 56

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This paper cites Scikit-learn: Machine learning in Python,.

Data-driven Lake Water Quality Forecasting for Time Series with Missing Data using Machine Learning Scikit-learn: Machine learning in Python,

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