{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T15:20:25Z","timestamp":1777648825588,"version":"3.51.4"},"reference-count":26,"publisher":"IEEE","license":[{"start":{"date-parts":[[2025,10,16]],"date-time":"2025-10-16T00:00:00Z","timestamp":1760572800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,10,16]],"date-time":"2025-10-16T00:00:00Z","timestamp":1760572800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,10,16]]},"DOI":"10.1109\/iccp68926.2025.11427141","type":"proceedings-article","created":{"date-parts":[[2026,3,13]],"date-time":"2026-03-13T19:51:37Z","timestamp":1773431497000},"page":"1-8","source":"Crossref","is-referenced-by-count":1,"title":["Energy Foresight: Predicting Daily Demand with Combined Techniques"],"prefix":"10.1109","author":[{"given":"Elena","family":"Hadarau","sequence":"first","affiliation":[{"name":"Technical University of Cluj-Napoca,Computer Science Department"}]},{"given":"Raluca","family":"Portase","sequence":"additional","affiliation":[{"name":"Technical University of Cluj-Napoca,Computer Science Department"}]},{"given":"Rodica","family":"Potolea","sequence":"additional","affiliation":[{"name":"Technical University of Cluj-Napoca,Computer Science Department"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.3390\/en15238919"},{"issue":"12","key":"ref2","doi-asserted-by":"crossref","DOI":"10.3390\/electronics13122325","article-title":"From individual device usage to household energy consumption profiling","volume":"13","author":"Tolas","year":"2024","journal-title":"Electronics"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4419-0320-4"},{"key":"ref4","article-title":"Modern Time Series Forecasting with Python: Industry-ready machine learning and deep learning time series analysis with PyTorch and pandas","volume-title":"Packt Publishing","author":"Joseph"},{"key":"ref5","article-title":"Forecasting: Principles and Practice","author":"Hyndman","year":"2021","journal-title":"Melbourne: OTexts"},{"issue":"7","key":"ref6","doi-asserted-by":"crossref","DOI":"10.3390\/s24072159","article-title":"Smartlaundry: A realtime system for public laundry allocation in smart cities","volume":"24","author":"Portase","year":"2024","journal-title":"Sensors"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.3390\/su152215860"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/apcit62007.2024.10673558"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1186\/s42162-022-00212-9"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.energy.2020.117948"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.3390\/en11040949"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ICCP.2018.8516617"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.5220\/0010655100003064"},{"issue":"4","key":"ref14","first-page":"1","article-title":"Data preprocessing in electrical energy consumption profile clustering studies","volume":"8","author":"\u015fen Y\u0131ld\u0131z","year":"2023","journal-title":"International Journal of Advances in Computer and Electronics Engineering"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1007\/s40747-022-00952-x"},{"issue":"5","key":"ref16","doi-asserted-by":"crossref","first-page":"1960","DOI":"10.3390\/app14051960","article-title":"Time series feature selection method based on mutual information","volume":"14","author":"Huang","year":"2024","journal-title":"Applied Sciences"},{"key":"ref17","volume-title":"Introduction to Time Series Analysis and Forecasting.","author":"Montgomery"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ICNN.1995.488968"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939785"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.3390\/a17080322"},{"key":"ref21","volume-title":"Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow. Sebastopol: O\u2019Reilly Media","author":"G\u00e9ron","year":"2019"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-24797-2"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.aei.2021.101442"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0282810"},{"key":"ref25","article-title":"Hourly energy consumption","author":"Williams","year":"2019"},{"key":"ref26","article-title":"What is pjm?","year":"2025","journal-title":"PJM Interconnection"}],"event":{"name":"2025 IEEE 21st International Conference on Intelligent Computer Communication and Processing (ICCP)","location":"Cluj-Napoca, Romania","start":{"date-parts":[[2025,10,16]]},"end":{"date-parts":[[2025,10,18]]}},"container-title":["2025 IEEE 21st International Conference on Intelligent Computer Communication and Processing (ICCP)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11427093\/11427059\/11427141.pdf?arnumber=11427141","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,16]],"date-time":"2026-03-16T20:10:32Z","timestamp":1773691832000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11427141\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,16]]},"references-count":26,"URL":"https:\/\/doi.org\/10.1109\/iccp68926.2025.11427141","relation":{},"subject":[],"published":{"date-parts":[[2025,10,16]]}}}