{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T01:35:31Z","timestamp":1785548131575,"version":"3.56.0"},"reference-count":37,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"name":"Department of Scientific and Industrial Research (DSIR), Government of India","award":["A2KS -11011\/7\/2022-IRD (SC)- DSIR"],"award-info":[{"award-number":["A2KS -11011\/7\/2022-IRD (SC)- DSIR"]}]},{"name":"Government of Gujarat, India","award":["GUJCOST\/STI\/2021-2022\/3922"],"award-info":[{"award-number":["GUJCOST\/STI\/2021-2022\/3922"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2024]]},"DOI":"10.1109\/access.2024.3373552","type":"journal-article","created":{"date-parts":[[2024,3,4]],"date-time":"2024-03-04T19:18:47Z","timestamp":1709579927000},"page":"36764-36777","source":"Crossref","is-referenced-by-count":38,"title":["Enhancing Household Energy Consumption Predictions Through Explainable AI Frameworks"],"prefix":"10.1109","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-2630-9732","authenticated-orcid":false,"given":"Aakash","family":"Bhandary","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, School of Technology, Pandit Deendayal Energy University, Gandhinagar, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-3372-4747","authenticated-orcid":false,"given":"Vruti","family":"Dobariya","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, School of Technology, Pandit Deendayal Energy University, Gandhinagar, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9146-8378","authenticated-orcid":false,"given":"Gokul","family":"Yenduri","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, VIT-AP University, Amaravati, Andhra Pradesh, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3285-7346","authenticated-orcid":false,"given":"Rutvij H.","family":"Jhaveri","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, School of Technology, Pandit Deendayal Energy University, Gandhinagar, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4583-9208","authenticated-orcid":false,"given":"Saikat","family":"Gochhait","sequence":"additional","affiliation":[{"name":"Symbiosis Institute of Digital and Telecom Management, Constituent of Symbiosis International Deemed University, Pune, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9203-1642","authenticated-orcid":false,"given":"Francesco","family":"Benedetto","sequence":"additional","affiliation":[{"name":"Department of Economics, Signal Processing for Telecommunications and Economics, Roma Tre University, Rome, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1145\/3334480.3383051"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.egyai.2022.100169"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2022.3153277"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2870052"},{"key":"ref5","first-page":"4768","article-title":"A unified approach to interpreting model predictions","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"30","author":"Lundberg"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/N16-3020"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1126\/scirobotics.aay7120"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2019.12.012"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1145\/3571306.3571443"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1145\/3397481.3450650"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.3390\/electronics11182947"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1057\/s41274-016-0150-y"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2019.00516"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3031477"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.3390\/en11040949"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-021-06773-2"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-19-4676-9_8"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.3390\/make3010009"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-10-7563-6_53"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.3390\/technologies9030052"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1017\/psrm.2017.4"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1027\/1015-5759.23.4.227"},{"issue":"9","key":"ref23","first-page":"1","article-title":"Pandas: A foundational Python library for data analysis and statistics","volume":"14","author":"McKinney","year":"2011","journal-title":"Python High Perform. Sci. Comput."},{"key":"ref24","volume-title":"Guide to Numpy","volume":"1","author":"Oliphant","year":"2006"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-00296-0_5"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1177\/154405910408300516"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/BigData47090.2019.9005997"},{"key":"ref28","first-page":"3149","article-title":"LightGBM: A highly efficient gradient boosting decision tree","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"30","author":"Ke"},{"key":"ref29","first-page":"6639","article-title":"CatBoost: Unbiased boosting with categorical features","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"31","author":"Prokhorenkova"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939785"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1016\/j.tra.2018.02.009"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-022-27059-0"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1016\/j.proeng.2017.09.615"},{"key":"ref34","article-title":"Adam: A method for stochastic optimization","author":"Kingma","year":"2014","journal-title":"arXiv:1412.6980"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.4018\/IJSIR.2021040101"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.7717\/peerj-cs.623"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1016\/S1574-0005(02)03016-3"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/10380310\/10459177.pdf?arnumber=10459177","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,19]],"date-time":"2024-07-19T05:51:42Z","timestamp":1721368302000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10459177\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"references-count":37,"URL":"https:\/\/doi.org\/10.1109\/access.2024.3373552","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]}}}