{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,26]],"date-time":"2026-09-26T05:25:04Z","timestamp":1790400304562,"version":"4.1.0"},"publisher-location":"Cham","reference-count":11,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031820724","type":"print"},{"value":"9783031820731","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025]]},"DOI":"10.1007\/978-3-031-82073-1_9","type":"book-chapter","created":{"date-parts":[[2025,2,17]],"date-time":"2025-02-17T18:27:39Z","timestamp":1739816859000},"page":"88-98","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["An Explainable AI-Based Demand Response Optimization Framework for\u00a0Smart Buildings"],"prefix":"10.1007","author":[{"given":"Muhammad","family":"Ibrar","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hayla","family":"Nahom","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Abegaz","family":"Mohammed","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sergio","family":"M\u00e1rquez-S\u00e1nchez","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Javier Hernandez","family":"Fernandez","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Juan Manuel","family":"Corchado","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aiman","family":"Erbad","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,2,18]]},"reference":[{"issue":"10","key":"9_CR1","doi-asserted-by":"publisher","first-page":"2663","DOI":"10.3390\/buildings13102663","volume":"13","author":"R Jurjevic","year":"2023","unstructured":"Jurjevic, R., Zakula, T.: Demand response in buildings: a comprehensive overview of current trends, approaches, and strategies. Buildings 13(10), 2663 (2023)","journal-title":"Buildings"},{"key":"9_CR2","doi-asserted-by":"publisher","first-page":"100121","DOI":"10.1016\/j.egyai.2021.100121","volume":"7","author":"F Pallonetto","year":"2022","unstructured":"Pallonetto, F., Jin, C., Mangina, E.: Forecast electricity demand in commercial building with machine learning models to enable demand response programs. Energy AI 7, 100121 (2022)","journal-title":"Energy AI"},{"key":"9_CR3","doi-asserted-by":"publisher","first-page":"100204","DOI":"10.1016\/j.egyai.2022.100204","volume":"11","author":"D Jang","year":"2023","unstructured":"Jang, D., Spangher, L., Nadarajah, S., Spanos, C.: Deep reinforcement learning with planning guardrails for building energy demand response. Energy AI 11, 100204 (2023)","journal-title":"Energy AI"},{"issue":"8","key":"9_CR4","first-page":"8554","volume":"69","author":"L Renzhi","year":"2021","unstructured":"Renzhi, L., et al.: Deep reinforcement learning-based demand response for smart facilities energy management. IEEE Trans. Industr. Electron. 69(8), 8554\u20138565 (2021)","journal-title":"IEEE Trans. Industr. Electron."},{"key":"9_CR5","doi-asserted-by":"crossref","unstructured":"Wang, X., Wang, H., Bhandari, B., Cheng, L.: Ai-empowered methods for smart energy consumption: a review of load forecasting, anomaly detection and demand response. Int. J. Precis. Eng. Manuf.-Green Technol. 1\u201331 (2023)","DOI":"10.1007\/s40684-023-00537-0"},{"key":"9_CR6","doi-asserted-by":"crossref","unstructured":"Javed, A.R., Ahmed, W., Pandya, S., Maddikunta, P.K.R., Alazab, M., Gadekallu, T.R.: A survey of explainable artificial intelligence for smart cities. Electronics 12(4), 1020 (2023)","DOI":"10.3390\/electronics12041020"},{"key":"9_CR7","doi-asserted-by":"crossref","unstructured":"Balakumar, P., Ramu, S.K., Vinopraba, T.: Dynamic pricing for load shifting: reducing electric vehicle charging impacts on the grid through machine learning-based demand response. Sustain. Cities Soc. 105256 (2024)","DOI":"10.1016\/j.scs.2024.105256"},{"key":"9_CR8","doi-asserted-by":"publisher","first-page":"100169","DOI":"10.1016\/j.egyai.2022.100169","volume":"9","author":"R Machlev","year":"2022","unstructured":"Machlev, R., et al.: Explainable artificial intelligence (XAI) techniques for energy and power systems: review, challenges and opportunities. Energy AI 9, 100169 (2022)","journal-title":"Energy AI"},{"issue":"6","key":"9_CR9","doi-asserted-by":"publisher","first-page":"4040","DOI":"10.3390\/app13064040","volume":"13","author":"A Dobrovolskis","year":"2023","unstructured":"Dobrovolskis, A., Kazanavi\u010dius, E., Ki\u017eauskien\u0117, L.: Building XAI-based agents for IoT systems. Appl. Sci. 13(6), 4040 (2023)","journal-title":"Appl. Sci."},{"key":"9_CR10","doi-asserted-by":"crossref","unstructured":"Pang, X., Luan, C., Liu, L., Liu, W., Zhu, Y.: Data-driven random forest forecasting method of monthly electricity consumption. Electr. Eng. 1\u201315 (2022)","DOI":"10.1007\/s00202-021-01457-5"},{"key":"9_CR11","doi-asserted-by":"crossref","unstructured":"van Tilburg, J, Siebert, L.C., Cremer, J.L.: MARL-iDR: multi-agent reinforcement learning for incentive-based residential demand response. In: 2023 IEEE Belgrade PowerTech, pp. 1\u20138 (2023)","DOI":"10.1109\/PowerTech55446.2023.10202941"}],"container-title":["Lecture Notes in Networks and Systems","Distributed Computing and Artificial Intelligence, 21st International Conference"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-82073-1_9","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,2,17]],"date-time":"2025-02-17T18:27:43Z","timestamp":1739816863000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-82073-1_9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9783031820724","9783031820731"],"references-count":11,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-82073-1_9","relation":{},"ISSN":["2367-3370","2367-3389"],"issn-type":[{"value":"2367-3370","type":"print"},{"value":"2367-3389","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"18 February 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"The authors have no competing interests to declare that are relevant to the content of this article.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Disclosure of Interests"}},{"value":"DCAI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Symposium on Distributed Computing and Artificial Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Salamanca","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Spain","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25 June 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 June 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"dcai2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.dcai-conference.net\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}