{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,8]],"date-time":"2025-10-08T16:07:27Z","timestamp":1759939647535,"version":"3.40.3"},"publisher-location":"Cham","reference-count":17,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030637989"},{"type":"electronic","value":"9783030637996"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-3-030-63799-6_18","type":"book-chapter","created":{"date-parts":[[2020,12,8]],"date-time":"2020-12-08T00:56:03Z","timestamp":1607388963000},"page":"227-240","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Short-Term Forecasting Methodology for Energy Demand in Residential Buildings and the Impact of the COVID-19 Pandemic on Forecasts"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7089-2823","authenticated-orcid":false,"given":"Meritxell","family":"Gomez-Omella","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6542-2878","authenticated-orcid":false,"given":"Iker","family":"Esnaola-Gonzalez","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Susana","family":"Ferreiro","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,12,8]]},"reference":[{"key":"18_CR1","doi-asserted-by":"publisher","first-page":"198","DOI":"10.1016\/j.enbuild.2016.06.089","volume":"128","author":"X Cao","year":"2016","unstructured":"Cao, X., Dai, X., Liu, J.: Building energy-consumption status worldwide and the state-of-the-art technologies for zero-energy buildings during the past decade. Energy Build. 128, 198\u2013213 (2016)","journal-title":"Energy Build."},{"key":"18_CR2","unstructured":"Global Alliance for Buildings and Construction, International Energy Agency and the United Nations Environment Programme. 2019 global status report for buildings and construction: Towards a zero-emission, efficient and resilient buildings and construction sector. Technical report (2019)"},{"key":"18_CR3","doi-asserted-by":"crossref","unstructured":"Contreras, J., Asensio, M., de Quevedo, P.M., Mu\u00f1oz-Delgado, G., Montoya-Bueno, S.: Demand response modeling (chap. 4). In: Contreras, J., Asensio, M., de Quevedo, P.M., Mu\u00f1oz-Delgado, G., Montoya-Bueno, S. (eds.) Joint RES and Distribution Network Expansion Planning Under a Demand Response Framework, pp. 33\u201340. Academic Press (2016)","DOI":"10.1016\/B978-0-12-805322-5.00004-6"},{"key":"18_CR4","doi-asserted-by":"publisher","first-page":"941","DOI":"10.1016\/j.rser.2013.09.009","volume":"29","author":"P Warren","year":"2014","unstructured":"Warren, P.: A review of demand-side management policy in the UK. Renew. Sustain. Energy Rev. 29, 941\u2013951 (2014)","journal-title":"Renew. Sustain. Energy Rev."},{"key":"18_CR5","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1016\/j.apenergy.2014.03.054","volume":"125","author":"C Bartusch","year":"2014","unstructured":"Bartusch, C., Alvehag, K.: Further exploring the potential of residential demand response programs in electricity distribution. Appl. Energy 125, 39\u201359 (2014)","journal-title":"Appl. Energy"},{"key":"18_CR6","unstructured":"Adhikari, R., Agrawal, R.K.: An introductory study on time series modeling and forecasting. Ph.D. thesis (2013)"},{"key":"18_CR7","unstructured":"Ben Taieb, S., Bontempi, G., Atiya, A.F., Sorjamaa, A.: A review and comparison of strategies for multi-step ahead time series forecasting based on the NN5 forecasting competition. Expert Syst. Appl. 39, 7067\u20137083 (2012)"},{"key":"18_CR8","doi-asserted-by":"publisher","first-page":"2019","DOI":"10.1007\/s10462-017-9593-z","volume":"52","author":"F Mart\u00ednez","year":"2019","unstructured":"Mart\u00ednez, F., Fr\u00edas, M.P., P\u00e9rez, M.D., Rivera, A.J.: A methodology for applying k-nearest neighbor to time series forecasting. Artif. Intell. Rev. 52, 2019\u20132037 (2019). https:\/\/doi.org\/10.1007\/s10462-017-9593-z","journal-title":"Artif. Intell. Rev."},{"key":"18_CR9","doi-asserted-by":"publisher","first-page":"221","DOI":"10.1089\/big.2018.0175","volume":"7","author":"HA Abu Alfeilat","year":"2019","unstructured":"Abu Alfeilat, H.A., et al.: Effects of distance measure choice on k-nearest neighbor classifier performance: a review. Big Data 7, 221\u2013248 (2019)","journal-title":"Big Data"},{"key":"18_CR10","volume-title":"Feature Engineering for Machine Learning","author":"A Zheng","year":"2018","unstructured":"Zheng, A., Casari, A.: Feature Engineering for Machine Learning. O\u2019Reilly Media, Inc., Sebastopol (2018)"},{"key":"18_CR11","series-title":"Lecture Notes in Business Information Processing","doi-asserted-by":"publisher","first-page":"62","DOI":"10.1007\/978-3-642-36318-4_3","volume-title":"Business Intelligence","author":"G Bontempi","year":"2013","unstructured":"Bontempi, G., Ben Taieb, S., Le Borgne, Y.-A.: Machine learning strategies for time series forecasting. In: Aufaure, M.-A., Zim\u00e1nyi, E. (eds.) eBISS 2012. LNBIP, vol. 138, pp. 62\u201377. Springer, Heidelberg (2013). https:\/\/doi.org\/10.1007\/978-3-642-36318-4_3"},{"key":"18_CR12","doi-asserted-by":"publisher","first-page":"451","DOI":"10.32614\/RJ-2016-058","volume":"8","author":"U Mori","year":"2016","unstructured":"Mori, U., Mendiburu, A., Lozano, J.A.: Distance measures for time series in R: the TSdist package. R J. 8, 451 (2016)","journal-title":"R J."},{"key":"18_CR13","unstructured":"Berndt, D., Clifford, J.: Using dynamic time warping to find patterns in time series. In: Workshop on Knowledge Knowledge Discovery in Databases (1994)"},{"key":"18_CR14","doi-asserted-by":"crossref","unstructured":"Chen, L., \u00d6zsu, M.T., Oria, V.: Robust and fast similarity search for moving object trajectories. In: Proceedings of the ACM SIGMOD International Conference on Management of Data (2005)","DOI":"10.1145\/1066157.1066213"},{"key":"18_CR15","unstructured":"Esnaola-Gonzalez, I., Diez, F.J., Pujic, D., Jelic, M., Tomasevic, N.: An artificial intelligent system for demand response in neighbourhoods. In: AIPES - The Workshop on Artificial Intelligence in Power and Energy Systems (Accepted, to be published)"},{"key":"18_CR16","doi-asserted-by":"publisher","first-page":"654","DOI":"10.1016\/j.apenergy.2017.07.114","volume":"205","author":"P Lusis","year":"2017","unstructured":"Lusis, P., Khalilpour, K.R., Andrew, L., Liebman, A.: Short-term residential load forecasting: impact of calendar effects and forecast granularity. Appl. Energy 205, 654\u2013669 (2017)","journal-title":"Appl. Energy"},{"issue":"1","key":"18_CR17","doi-asserted-by":"publisher","first-page":"69","DOI":"10.1023\/A:1018046501280","volume":"23","author":"G Widmer","year":"1996","unstructured":"Widmer, G., Kubat, M.: Learning in the presence of concept drift and hidden contexts. Mach. Learn. 23(1), 69\u2013101 (1996). https:\/\/doi.org\/10.1023\/A:1018046501280","journal-title":"Mach. Learn."}],"container-title":["Lecture Notes in Computer Science","Artificial Intelligence XXXVII"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-63799-6_18","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,4,24]],"date-time":"2021-04-24T23:57:33Z","timestamp":1619308653000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-63799-6_18"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030637989","9783030637996"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-63799-6_18","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"8 December 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"SGAI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Innovative Techniques and Applications of Artificial Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Cambridge","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"United Kingdom","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 December 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 December 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"40","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"sgai2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/bcs-sgai.org\/ai2020\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}