{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:XUNIOJ3DRBIBBCV6USOALQVH5Z","short_pith_number":"pith:XUNIOJ3D","schema_version":"1.0","canonical_sha256":"bd1a8727638850108abea49c05c2a7ee5c8810d323bf0799eea2406c97babf91","source":{"kind":"arxiv","id":"1810.10619","version":1},"attestation_state":"computed","paper":{"title":"Using Personal Environmental Comfort Systems to Mitigate the Impact of Occupancy Prediction Errors on HVAC Performance","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.SY","authors_text":"Catherine Rosenberg, Milan Jain, Rachel K Kalaimani, Srinivasan Keshav","submitted_at":"2018-10-24T21:08:27Z","abstract_excerpt":"Heating, Ventilation and Air Conditioning (HVAC) consumes a significant fraction of energy in commercial buildings. Hence, the use of optimization techniques to reduce HVAC energy consumption has been widely studied. Model predictive control (MPC) is one state of the art optimization technique for HVAC control which converts the control problem to a sequence of optimization problems, each over a finite time horizon. In a typical MPC, future system state is estimated from a model using predictions of model inputs, such as building occupancy and outside air temperature. Consequently, as predicti"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1810.10619","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.SY","submitted_at":"2018-10-24T21:08:27Z","cross_cats_sorted":[],"title_canon_sha256":"8f9bfab2c3b61f17ee7bcae52beb1468c97402ccfdcb0a8c8cc85d7d7de91877","abstract_canon_sha256":"1051c1b810005268390bb67d7cb8bfa0a25033bb7f716f749a8e85c6e60d85e1"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:02:20.058802Z","signature_b64":"E5CXcRmdKC8AqUkyBxh2mRHjKLhdy1+p5Xc24rRAb4sYnxOEPRw79OgWfnVsiElIQfw+Dtv3wDKjI3v3FebmDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bd1a8727638850108abea49c05c2a7ee5c8810d323bf0799eea2406c97babf91","last_reissued_at":"2026-05-18T00:02:20.058453Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:02:20.058453Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Using Personal Environmental Comfort Systems to Mitigate the Impact of Occupancy Prediction Errors on HVAC Performance","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.SY","authors_text":"Catherine Rosenberg, Milan Jain, Rachel K Kalaimani, Srinivasan Keshav","submitted_at":"2018-10-24T21:08:27Z","abstract_excerpt":"Heating, Ventilation and Air Conditioning (HVAC) consumes a significant fraction of energy in commercial buildings. Hence, the use of optimization techniques to reduce HVAC energy consumption has been widely studied. Model predictive control (MPC) is one state of the art optimization technique for HVAC control which converts the control problem to a sequence of optimization problems, each over a finite time horizon. In a typical MPC, future system state is estimated from a model using predictions of model inputs, such as building occupancy and outside air temperature. Consequently, as predicti"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1810.10619","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"1810.10619","created_at":"2026-05-18T00:02:20.058510+00:00"},{"alias_kind":"arxiv_version","alias_value":"1810.10619v1","created_at":"2026-05-18T00:02:20.058510+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1810.10619","created_at":"2026-05-18T00:02:20.058510+00:00"},{"alias_kind":"pith_short_12","alias_value":"XUNIOJ3DRBIB","created_at":"2026-05-18T12:33:01.666342+00:00"},{"alias_kind":"pith_short_16","alias_value":"XUNIOJ3DRBIBBCV6","created_at":"2026-05-18T12:33:01.666342+00:00"},{"alias_kind":"pith_short_8","alias_value":"XUNIOJ3D","created_at":"2026-05-18T12:33:01.666342+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/XUNIOJ3DRBIBBCV6USOALQVH5Z","json":"https://pith.science/pith/XUNIOJ3DRBIBBCV6USOALQVH5Z.json","graph_json":"https://pith.science/api/pith-number/XUNIOJ3DRBIBBCV6USOALQVH5Z/graph.json","events_json":"https://pith.science/api/pith-number/XUNIOJ3DRBIBBCV6USOALQVH5Z/events.json","paper":"https://pith.science/paper/XUNIOJ3D"},"agent_actions":{"view_html":"https://pith.science/pith/XUNIOJ3DRBIBBCV6USOALQVH5Z","download_json":"https://pith.science/pith/XUNIOJ3DRBIBBCV6USOALQVH5Z.json","view_paper":"https://pith.science/paper/XUNIOJ3D","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1810.10619&json=true","fetch_graph":"https://pith.science/api/pith-number/XUNIOJ3DRBIBBCV6USOALQVH5Z/graph.json","fetch_events":"https://pith.science/api/pith-number/XUNIOJ3DRBIBBCV6USOALQVH5Z/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/XUNIOJ3DRBIBBCV6USOALQVH5Z/action/timestamp_anchor","attest_storage":"https://pith.science/pith/XUNIOJ3DRBIBBCV6USOALQVH5Z/action/storage_attestation","attest_author":"https://pith.science/pith/XUNIOJ3DRBIBBCV6USOALQVH5Z/action/author_attestation","sign_citation":"https://pith.science/pith/XUNIOJ3DRBIBBCV6USOALQVH5Z/action/citation_signature","submit_replication":"https://pith.science/pith/XUNIOJ3DRBIBBCV6USOALQVH5Z/action/replication_record"}},"created_at":"2026-05-18T00:02:20.058510+00:00","updated_at":"2026-05-18T00:02:20.058510+00:00"}