{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,19]],"date-time":"2026-05-19T04:21:11Z","timestamp":1779164471712,"version":"3.51.4"},"reference-count":208,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"6","license":[{"start":{"date-parts":[[2025,3,15]],"date-time":"2025-03-15T00:00:00Z","timestamp":1741996800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,3,15]],"date-time":"2025-03-15T00:00:00Z","timestamp":1741996800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,3,15]],"date-time":"2025-03-15T00:00:00Z","timestamp":1741996800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001381","name":"National Research Foundation, Singapore and Infocomm Media Development Authority under its Future Communications Research and Development Programme","doi-asserted-by":"publisher","award":["FCP-SIT-TG-2022-007"],"award-info":[{"award-number":["FCP-SIT-TG-2022-007"]}],"id":[{"id":"10.13039\/501100001381","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Defence Science Organisation (DSO) National Laboratories under the AI Singapore Programme","award":["FCP-NTU-RG-2022-010"],"award-info":[{"award-number":["FCP-NTU-RG-2022-010"]}]},{"name":"Defence Science Organisation (DSO) National Laboratories under the AI Singapore Programme","award":["FCP-ASTAR-TG-2022-003"],"award-info":[{"award-number":["FCP-ASTAR-TG-2022-003"]}]},{"name":"Singapore Ministry of Education (MOE) Tier 1","award":["RG87\/22"],"award-info":[{"award-number":["RG87\/22"]}]},{"DOI":"10.13039\/100018102","name":"NTU Centre for Computational Technologies in Finance","doi-asserted-by":"publisher","award":["NTU-CCTF"],"award-info":[{"award-number":["NTU-CCTF"]}],"id":[{"id":"10.13039\/100018102","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Seitee Pte Ltd., A*STAR under its MTC Programmatic","award":["M23L9b0052"],"award-info":[{"award-number":["M23L9b0052"]}]},{"name":"MTC Individual Research Grants","award":["M23M6c0113"],"award-info":[{"award-number":["M23M6c0113"]}]},{"name":"Ministry of Education, Singapore, under the Academic Research Tier 1 Grant","award":["GMS 693"],"award-info":[{"award-number":["GMS 693"]}]},{"name":"SIT\u2019s Ignition Grant","award":["IG (S) 2\/2023\u2013792"],"award-info":[{"award-number":["IG (S) 2\/2023\u2013792"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Internet Things J."],"published-print":{"date-parts":[[2025,3,15]]},"DOI":"10.1109\/jiot.2024.3511961","type":"journal-article","created":{"date-parts":[[2024,12,5]],"date-time":"2024-12-05T19:15:36Z","timestamp":1733426136000},"page":"6208-6232","source":"Crossref","is-referenced-by-count":20,"title":["The Role of Generative Artificial Intelligence in Internet of Electric Vehicles"],"prefix":"10.1109","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6295-4753","authenticated-orcid":false,"given":"Hanwen","family":"Zhang","sequence":"first","affiliation":[{"name":"College of Computing and Data Science, Nanyang Technological University, Jurong West, Singapore"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7442-7416","authenticated-orcid":false,"given":"Dusit","family":"Niyato","sequence":"additional","affiliation":[{"name":"College of Computing and Data Science, Nanyang Technological University, Jurong West, Singapore"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2644-2582","authenticated-orcid":false,"given":"Wei","family":"Zhang","sequence":"additional","affiliation":[{"name":"Singapore Institute of Technology, Dover Dr, Singapore"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9187-9572","authenticated-orcid":false,"given":"Changyuan","family":"Zhao","sequence":"additional","affiliation":[{"name":"College of Computing and Data Science, Nanyang Technological University, Jurong West, Singapore"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8220-6525","authenticated-orcid":false,"given":"Hongyang","family":"Du","sequence":"additional","affiliation":[{"name":"Department of Electrical and Electronic Engineering, University of Hong Kong, Hong Kong, SAR, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1807-7220","authenticated-orcid":false,"given":"Abbas","family":"Jamalipour","sequence":"additional","affiliation":[{"name":"School of Electrical and Computer Engineering, The University of Sydney, Sydney, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1701-8122","authenticated-orcid":false,"given":"Sumei","family":"Sun","sequence":"additional","affiliation":[{"name":"Singapore Institute of Technology, Dover Dr, Singapore"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9915-8697","authenticated-orcid":false,"given":"Yiyang","family":"Pei","sequence":"additional","affiliation":[{"name":"Singapore Institute of Technology, Dover Dr, Singapore"}]}],"member":"263","reference":[{"key":"ref1","volume-title":"Are U.S. EV sales a disaster or a booming segment? The answer may be both","author":"Becker","year":"2024"},{"key":"ref2","volume-title":"China\u2019s EV growth set to explode in 2024","year":"2024"},{"key":"ref3","volume-title":"Electric vehicle market\u2014Global industry assessment & forecast","year":"2024"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2023.3304718"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2023.3331600"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2024.3383876"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2023.3319588"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2023.3315483"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2023.3340155"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/JSYST.2020.3043327"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TTE.2020.3033995"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TIV.2022.3168577"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2023.3281552"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.3390\/en12050849"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.3390\/su15032105"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1016\/j.epsr.2022.108247"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TIV.2023.3328458"},{"key":"ref18","volume-title":"Battery states: State of charge (SoC), state of health (SoH). Electrochemistry basics series","year":"2023"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1706.03762"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/AIoT63253.2024.00048"},{"key":"ref21","article-title":"Nutrition estimation for dietary management: A transformer approach with depth sensing","author":"Kwan","year":"2024","journal-title":"arXiv:2406.01938"},{"key":"ref22","article-title":"Robust speech recognition via large-scale weak supervision","author":"Radford","year":"2022","journal-title":"arXiv:2212.04356"},{"key":"ref23","article-title":"ViLT: Vision-and-language transformer without convolution or region supervision","author":"Kim","year":"2021","journal-title":"arXiv:2102.03334"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.patter.2020.100195"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2023.121949"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2023.121711"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2023.3276947"},{"key":"ref28","first-page":"1","article-title":"Generative adversarial nets","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"27","author":"Goodfellow"},{"key":"ref29","article-title":"Unsupervised representation learning with deep convolutional generative adversarial networks","author":"Radford","year":"2015","journal-title":"arXiv:1511.06434"},{"key":"ref30","article-title":"Progressive growing of GANs for improved quality, stability, and variation","author":"Karras","year":"2017","journal-title":"arXiv:1710.10196"},{"key":"ref31","first-page":"214","article-title":"Wasserstein generative adversarial networks","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Arjovsky"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00453"},{"key":"ref33","article-title":"Evolving semantic communication with generative model","author":"Tang","year":"2024","journal-title":"arXiv:2403.20237"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP49357.2023.10096372"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00559"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1016\/j.est.2023.110004"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/EI252483.2021.9713417"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.17775\/CSEEJPES.2022.05640"},{"key":"ref39","first-page":"1","article-title":"Adversarial attacks on deep reinforcement learning applications in electric vehicle charging scheduling: A dual-stage attack framework","volume-title":"Proc. SSRN","author":"Peng"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.3389\/fenrg.2022.1013154"},{"key":"ref41","first-page":"5689","article-title":"GAIN: Missing data imputation using generative adversarial nets","volume-title":"Proc. 35th Int. Conf. Mach. Learn.","volume":"80","author":"Yoon"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.278"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.478"},{"key":"ref44","first-page":"22243","article-title":"Big self-supervised models are strong semi-supervised learners","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"33","author":"Chen"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/tte.2024.3355094"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/tte.2024.3363672"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2023.3294349"},{"key":"ref48","article-title":"Semantic facial expression editing using autoencoded flow","author":"Yeh","year":"2016","journal-title":"arXiv:1611.09961"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46478-7_51"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00842"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2022.109903"},{"key":"ref52","first-page":"6840","article-title":"Denoising diffusion probabilistic models","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"33","author":"Ho"},{"key":"ref53","article-title":"Denoising diffusion implicit models","author":"Song","year":"2020","journal-title":"arXiv:2010.02502"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01042"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.00355"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/COMST.2024.3400011"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2024.3377226"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2024.3414628"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1109\/MWC.013.2300485"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.3390\/en16093815"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2024.3360874"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1080\/14765284.2023.2245279"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijmedinf.2024.105474"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.46328\/ijte.845"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1016\/j.jpowsour.2023.233472"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2023.110281"},{"key":"ref67","volume-title":"Mitigating EV battery fires with infrared technology","year":"2024"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-020-58021-7"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1016\/j.est.2020.101957"},{"key":"ref70","doi-asserted-by":"publisher","DOI":"10.1002\/aenm.202003868"},{"key":"ref71","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2019.113381"},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2019.113648"},{"key":"ref73","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM50108.2020.00093"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.1109\/TPEL.2020.3008194"},{"key":"ref75","volume-title":"The risk of lithium-ion batteries\u2014Thermal runaway in EV\u2019s","author":"Smol","year":"2024"},{"key":"ref76","doi-asserted-by":"publisher","DOI":"10.1016\/j.isci.2022.104172"},{"key":"ref77","volume-title":"Exploring BMS state of charge (SOC): Monitoring battery health","year":"2024"},{"key":"ref78","doi-asserted-by":"publisher","DOI":"10.1016\/j.jpowsour.2020.229154"},{"key":"ref79","doi-asserted-by":"publisher","DOI":"10.1016\/j.jpowsour.2023.232737"},{"key":"ref80","doi-asserted-by":"publisher","DOI":"10.1016\/j.energy.2022.124468"},{"key":"ref81","doi-asserted-by":"publisher","DOI":"10.1016\/j.energy.2022.124612"},{"key":"ref82","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2912803"},{"key":"ref83","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2020.3046036"},{"key":"ref84","doi-asserted-by":"publisher","DOI":"10.1145\/3490354.3494393"},{"key":"ref85","doi-asserted-by":"publisher","DOI":"10.1109\/PowerAfrica52236.2021.9543237"},{"key":"ref86","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2022.120516"},{"key":"ref87","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2896409"},{"key":"ref88","doi-asserted-by":"publisher","DOI":"10.3390\/en14123692"},{"key":"ref89","doi-asserted-by":"publisher","DOI":"10.1109\/ITEC.2019.8790543"},{"key":"ref90","volume-title":"LG INR18650HG2","year":"2024"},{"key":"ref91","volume-title":"The importance of state of charge (SOC) and state of health (SOH) in battery management systems","year":"2024"},{"key":"ref92","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2021.3055068"},{"key":"ref93","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2020.115104"},{"key":"ref94","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2022.3148528"},{"key":"ref95","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2012.2222650"},{"key":"ref96","doi-asserted-by":"publisher","DOI":"10.1016\/j.energy.2016.06.130"},{"key":"ref97","doi-asserted-by":"publisher","DOI":"10.3390\/en15134594"},{"key":"ref98","doi-asserted-by":"publisher","DOI":"10.1016\/j.jpowsour.2019.03.008"},{"key":"ref99","doi-asserted-by":"publisher","DOI":"10.1016\/j.ifacol.2022.07.441"},{"key":"ref100","doi-asserted-by":"publisher","DOI":"10.1109\/TENCON50793.2020.9293872"},{"key":"ref101","doi-asserted-by":"publisher","DOI":"10.1115\/1.4053326"},{"key":"ref102","doi-asserted-by":"publisher","DOI":"10.1002\/er.6910"},{"key":"ref103","article-title":"Practical battery health monitoring using uncertainty-aware Bayesian neural network","author":"Zhao","year":"2024","journal-title":"arXiv:2404.14444"},{"key":"ref104","doi-asserted-by":"publisher","DOI":"10.1145\/3626235"},{"key":"ref105","doi-asserted-by":"publisher","DOI":"10.1038\/s41560-019-0356-8"},{"key":"ref106","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2022.3151975"},{"key":"ref107","first-page":"5244","article-title":"Enhancing the locality and breaking the memory bottleneck of transformer on time series forecasting","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"32","author":"Li"},{"key":"ref108","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2023.3288824"},{"key":"ref109","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2835825"},{"key":"ref110","doi-asserted-by":"publisher","DOI":"10.1016\/j.jclepro.2019.04.345"},{"key":"ref111","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2020.2975134"},{"key":"ref112","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2022.119616"},{"key":"ref113","doi-asserted-by":"publisher","DOI":"10.1016\/j.epsr.2022.108119"},{"key":"ref114","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2020.116125"},{"key":"ref115","volume-title":"My electric avenue data download","year":"2017"},{"key":"ref116","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2019.113732"},{"key":"ref117","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3103119"},{"key":"ref118","doi-asserted-by":"publisher","DOI":"10.1109\/ICPSAsia55496.2022.9949855"},{"key":"ref119","doi-asserted-by":"publisher","DOI":"10.1016\/j.mex.2024.102618"},{"key":"ref120","volume-title":"Dataset (TC1A): Basic profiling of domestic smart meter customers","year":"2014"},{"key":"ref121","volume-title":"Dataset (TC5): Enhanced profiling of domestic customers with solar photovoltaics (PV)","year":"2014"},{"key":"ref122","volume-title":"National travel survey, 2002\u20132020","year":"2021"},{"key":"ref123","doi-asserted-by":"publisher","DOI":"10.3390\/data5010017"},{"key":"ref124","doi-asserted-by":"publisher","DOI":"10.1016\/j.jksus.2021.101683"},{"key":"ref125","first-page":"1","article-title":"Pointer networks","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"28","author":"Vinyals"},{"key":"ref126","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.5723"},{"key":"ref127","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-022-03456-w"},{"key":"ref128","article-title":"Attention, learn to solve routing problems!","author":"Kool","year":"2018","journal-title":"arXiv:1803.08475"},{"key":"ref129","doi-asserted-by":"publisher","DOI":"10.1016\/j.tre.2011.08.001"},{"key":"ref130","volume-title":"Computer software: Gurobi optimizer (version 9.5)","year":"2022"},{"key":"ref131","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijpe.2018.07.016"},{"key":"ref132","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejor.2015.01.049"},{"key":"ref133","doi-asserted-by":"publisher","DOI":"10.1109\/MNET.2024.3391767"},{"key":"ref134","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2024.3439363"},{"key":"ref135","doi-asserted-by":"publisher","DOI":"10.1109\/JAS.2023.123744"},{"key":"ref136","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijepes.2022.108404"},{"key":"ref137","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2023.121614"},{"key":"ref138","first-page":"1603","article-title":"Multivariate time series imputation with generative adversarial networks","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"31","author":"Luo"},{"key":"ref139","article-title":"EVGen: Adversarial networks for learning electric vehicle charging loads and hidden representations","author":"Buechler","year":"2021","journal-title":"arXiv:2108.03762"},{"key":"ref140","doi-asserted-by":"publisher","DOI":"10.1016\/B978-044452044-9\/50005-7"},{"key":"ref141","volume-title":"5.2. piecewise linear interpolation\u2014Fundamentals of numerical computation","author":"Driscoll","year":"2022"},{"key":"ref142","doi-asserted-by":"publisher","DOI":"10.1016\/j.jss.2012.05.073"},{"key":"ref143","doi-asserted-by":"publisher","DOI":"10.1109\/APPEEC.2016.7779794"},{"key":"ref144","doi-asserted-by":"publisher","DOI":"10.1016\/j.enconman.2015.10.066"},{"key":"ref145","doi-asserted-by":"publisher","DOI":"10.1145\/3209978.3210006"},{"key":"ref146","doi-asserted-by":"publisher","DOI":"10.1109\/EPEC48502.2020.9319916"},{"key":"ref147","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijepes.2019.105586"},{"key":"ref148","first-page":"9117","article-title":"Temporal latent auto-encoder: A method for probabilistic multivariate time series forecasting","volume-title":"Proc. AAAI Conf. Artif. Intell.","volume":"35","author":"Nguyen"},{"key":"ref149","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i12.17325"},{"key":"ref150","volume-title":"Forecasting and analytics with the augmented dynamic adaptive model (ADAM)","author":"Svetunkov","year":"2024"},{"key":"ref151","article-title":"On first-order meta-learning algorithms","author":"Nichol","year":"2018","journal-title":"arXiv:1803.02999"},{"key":"ref152","doi-asserted-by":"publisher","DOI":"10.1145\/3307772.3328313"},{"key":"ref153","volume-title":"Smard platform","year":"2024"},{"key":"ref154","volume-title":"Inventory of U.S. greenhouse gas emissions and sinks","year":"2018"},{"key":"ref155","doi-asserted-by":"publisher","DOI":"10.17226\/12794"},{"key":"ref156","doi-asserted-by":"publisher","DOI":"10.1038\/s41893-020-0533-6"},{"key":"ref157","article-title":"BERT: Pre-training of deep bidirectional transformers for language understanding","author":"Devlin","year":"2018","journal-title":"arXiv:1810.04805"},{"key":"ref158","first-page":"5754","article-title":"XLNet: Generalized autoregressive pretraining for language understanding","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"32","author":"Yang"},{"key":"ref159","first-page":"22","article-title":"Evaluating electric vehicle user mobility data using neural network-based language models","volume-title":"Proc. Transp. Res. Board (TRB) Annual Meeting","author":"Alvarez"},{"key":"ref160","first-page":"260","article-title":"Machine learning with annotator rationales to reduce annotation cost","volume-title":"Proc. NIPS Workshop Cost Sensitive Learn.","author":"Zaidan"},{"key":"ref161","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P19-1282"},{"key":"ref162","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P17-1028"},{"key":"ref163","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2023.3306826"},{"key":"ref164","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2020.3015204"},{"key":"ref165","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2019.2955437"},{"key":"ref166","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2023.3309528"},{"key":"ref167","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2023.3250505"},{"key":"ref168","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2023.02.013"},{"key":"ref169","doi-asserted-by":"publisher","DOI":"10.1049\/cit2.12028"},{"key":"ref170","article-title":"Adversarial attacks on neural network policies","author":"Huang","year":"2017","journal-title":"arXiv:1702.02284"},{"key":"ref171","doi-asserted-by":"publisher","DOI":"10.1201\/9781351251389-8"},{"key":"ref172","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.282"},{"key":"ref173","article-title":"Adversarial attacks on reinforcement learning based energy management systems of extended range electric delivery vehicles","author":"Wang","year":"2020","journal-title":"arXiv:2006.00817"},{"key":"ref174","doi-asserted-by":"publisher","DOI":"10.1109\/TPWRS.2021.3107402"},{"key":"ref175","doi-asserted-by":"publisher","DOI":"10.1109\/TCSII.2022.3181827"},{"key":"ref176","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2888582"},{"key":"ref177","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2902910"},{"key":"ref178","doi-asserted-by":"publisher","DOI":"10.1109\/JSYST.2021.3109082"},{"key":"ref179","doi-asserted-by":"publisher","DOI":"10.3390\/en15113931"},{"key":"ref180","doi-asserted-by":"publisher","DOI":"10.2172\/1877784"},{"key":"ref181","doi-asserted-by":"publisher","DOI":"10.1109\/PST.2017.00017"},{"key":"ref182","volume-title":"ROAD: The real ORNL automotive dynamometer controller area network intrusion detection dataset (with a comprehensive can IDS dataset survey & guide)","author":"Verma","year":"2020"},{"key":"ref183","doi-asserted-by":"publisher","DOI":"10.1109\/RWS47064.2019.8972003"},{"key":"ref184","volume-title":"Open access same-time information system (OASIS)","year":"2024"},{"key":"ref185","doi-asserted-by":"publisher","DOI":"10.1038\/nature14236"},{"key":"ref186","article-title":"Continuous control with deep reinforcement learning","author":"Lillicrap","year":"2015","journal-title":"arXiv:1509.02971"},{"key":"ref187","article-title":"Proximal policy optimization algorithms","author":"Schulman","year":"2017","journal-title":"arXiv:1707.06347"},{"key":"ref188","first-page":"1861","article-title":"Soft actor\u2013critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Haarnoja"},{"key":"ref189","article-title":"Explaining and harnessing adversarial examples","author":"Goodfellow","year":"2014","journal-title":"arXiv:1412.6572"},{"key":"ref190","doi-asserted-by":"publisher","DOI":"10.1109\/VCC60689.2023.10475111"},{"key":"ref191","volume-title":"Residential power traces for five houses: The iHomeLab RAPT dataset","author":"Huber","year":"2019"},{"key":"ref192","doi-asserted-by":"publisher","DOI":"10.1109\/CAMAD52502.2021.9617787"},{"key":"ref193","volume-title":"Backcasted (actual) load profiles\u2014Historical","year":"2024"},{"key":"ref194","volume-title":"Can dataset for intrusion detection (OTIDS)","year":"2017"},{"key":"ref195","volume-title":"Car-hacking dataset for the intrusion detection","year":"2018"},{"key":"ref196","doi-asserted-by":"publisher","DOI":"10.1109\/PST.2018.8514157"},{"key":"ref197","doi-asserted-by":"publisher","DOI":"10.1109\/ISIE51358.2023.10228104"},{"key":"ref198","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2023.3331544"},{"key":"ref199","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2018.2829917"},{"key":"ref200","doi-asserted-by":"publisher","DOI":"10.1016\/j.egyr.2022.02.261"},{"key":"ref201","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2017.02.021"},{"key":"ref202","doi-asserted-by":"publisher","DOI":"10.1016\/j.energy.2022.123592"},{"key":"ref203","doi-asserted-by":"publisher","DOI":"10.1109\/PESGM46819.2021.9637844"},{"key":"ref204","first-page":"1","article-title":"Time-series generative adversarial networks","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"32","author":"Yoon"},{"key":"ref205","volume-title":"The public data open platform for new energy vehicles","year":"2024"},{"key":"ref206","volume-title":"City of boulder open data","year":"2021"},{"key":"ref207","volume-title":"Transparency on grid data","year":"2024"},{"key":"ref208","volume-title":"What was driving the project?","year":"2024"}],"container-title":["IEEE Internet of Things Journal"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6488907\/10918322\/10778265.pdf?arnumber=10778265","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,3,11]],"date-time":"2025-03-11T17:46:02Z","timestamp":1741715162000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10778265\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,3,15]]},"references-count":208,"journal-issue":{"issue":"6"},"URL":"https:\/\/doi.org\/10.1109\/jiot.2024.3511961","relation":{},"ISSN":["2327-4662","2372-2541"],"issn-type":[{"value":"2327-4662","type":"electronic"},{"value":"2372-2541","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,3,15]]}}}