{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,11]],"date-time":"2026-02-11T21:51:11Z","timestamp":1770846671427,"version":"3.50.1"},"reference-count":24,"publisher":"IEEE","license":[{"start":{"date-parts":[[2025,11,24]],"date-time":"2025-11-24T00:00:00Z","timestamp":1763942400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,11,24]],"date-time":"2025-11-24T00:00:00Z","timestamp":1763942400000},"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":[[2025,11,24]]},"DOI":"10.1109\/iccma67641.2025.11369643","type":"proceedings-article","created":{"date-parts":[[2026,2,5]],"date-time":"2026-02-05T20:38:48Z","timestamp":1770323928000},"page":"416-422","source":"Crossref","is-referenced-by-count":0,"title":["A Hybrid Weibull-Physics-Informed Neural Network Framework for Early Anomaly Detection in Lithium-Ion Batteries"],"prefix":"10.1109","author":[{"given":"Haneen","family":"Altartouri","sequence":"first","affiliation":[{"name":"Fujairah University,College of Engineering and Technology,Fujairah,UAE"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sahar","family":"Qaadan","sequence":"additional","affiliation":[{"name":"Jordanian University,Mechatronics Engineering German,Amman,Jordan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rami","family":"Alazrai","sequence":"additional","affiliation":[{"name":"Abdullah Al Salem University,College of Computer and Systems Engineering,Khaldiya,Kuwait"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Aiman","family":"Alshare","sequence":"additional","affiliation":[{"name":"German Jordanian University,Mechanical and Maintenance Engineering,Amman,Jordan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1039\/D1CP00359C"},{"key":"ref2","article-title":"Battery data set","author":"Saha","year":"2007"},{"key":"ref3","first-page":"290","article-title":"Modeling li-ion battery capacity depletion in a particle filtering framework","volume-title":"Proceedings of the Annual Conference of the Prognostics and Health Management Society","author":"Saha"},{"issue":"8","key":"ref4","first-page":"679","article-title":"A generative modeling framework for battery health prognostics","volume":"9","author":"Wu","year":"2016","journal-title":"Energies"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1038\/s41560-019-0356-8"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.dib.2025.111346"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/GPECOM65896.2025.11061985"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1007\/s11581-025-06431-w"},{"key":"ref9","first-page":"122010","article-title":"Physics-informed neural networks for building thermal modeling and demand response control","volume":"355","author":"Chen","year":"2024","journal-title":"Applied Energy"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/DDCLS66240.2025.11064966"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcp.2018.10.045"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.36001\/ijphm.2013.v4i1.1437"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.3390\/wevj16080429"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-024-48779-z"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.jpowsour.2004.02.031"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-84628-288-1_3"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1148\/radiology.143.1.7063747"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1145\/1143844.1143874"},{"issue":"1","key":"ref19","first-page":"37","article-title":"Evaluation: From precision, recall and f-measure to roc, informedness, markedness and correlation","volume":"2","author":"Powers","year":"2008","journal-title":"Journal of Machine Learning Technologies"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2005.10.010"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/0005-2795(75)90109-9"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1002\/9781118033005"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2021.116263"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/icdm.2008.17"}],"event":{"name":"2025 13th International Conference on Control, Mechatronics and Automation (ICCMA)","location":"Paris, France","start":{"date-parts":[[2025,11,24]]},"end":{"date-parts":[[2025,11,26]]}},"container-title":["2025 13th International Conference on Control, Mechatronics and Automation (ICCMA)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11369474\/11369481\/11369643.pdf?arnumber=11369643","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,11]],"date-time":"2026-02-11T20:54:02Z","timestamp":1770843242000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11369643\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,24]]},"references-count":24,"URL":"https:\/\/doi.org\/10.1109\/iccma67641.2025.11369643","relation":{},"subject":[],"published":{"date-parts":[[2025,11,24]]}}}