{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,30]],"date-time":"2025-10-30T07:16:58Z","timestamp":1761808618377,"version":"3.37.3"},"reference-count":16,"publisher":"IEEE","license":[{"start":{"date-parts":[[2023,5,10]],"date-time":"2023-05-10T00:00:00Z","timestamp":1683676800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,5,10]],"date-time":"2023-05-10T00:00:00Z","timestamp":1683676800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100005307","name":"DGRSDT Algeria (Direction G\u00e9n\u00e9rale de la recherche scientifique et du development technologique)","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100005307","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,5,10]]},"DOI":"10.1109\/iccad57653.2023.10152457","type":"proceedings-article","created":{"date-parts":[[2023,6,24]],"date-time":"2023-06-24T04:39:00Z","timestamp":1687581540000},"page":"1-5","source":"Crossref","is-referenced-by-count":4,"title":["Time Generative adversarial network for the generation of electricity load data"],"prefix":"10.1109","author":[{"given":"Snani","family":"Aissa","sequence":"first","affiliation":[{"name":"University Badji Mokhtar,LabGED,Department of computer science,Algeria,23000"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Khadir Mohamed","family":"Tarek","sequence":"additional","affiliation":[{"name":"University Badji Mokhtar,LabGED,Department of computer science,Algeria,23000"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref13","article-title":"Conditional Sig-Wasserstein GANs for Time Series Generation","author":"ni","year":"2023","journal-title":"arXiv Jun 09 2020"},{"key":"ref12","first-page":"1718","article-title":"Generative Moment Matching Networks","author":"li","year":"2015","journal-title":"Proceedings of The 32nd International Conference on Machine Learning"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.2203.11242"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1186\/s43067-020-00021-8"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1561\/2200000056"},{"key":"ref10","article-title":"Real-valued (Medical) Time Series Generation with Recurrent Conditional GANs","author":"esteban","year":"2023","journal-title":"arXiv Dec 03 2017"},{"key":"ref2","first-page":"2672","article-title":"Generative adversarial nets","author":"goodfellow","year":"2014","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref1","article-title":"Time-series generative adversarial networks","volume":"32","author":"yoon","year":"0","journal-title":"Advances in neural information processing systems"},{"key":"ref16","article-title":"Measuring the quality of Synthetic data for use in competitions","author":"jordon","year":"2023","journal-title":"arXiv Jun 29 2018"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/S0169-2070(97)00044-7"},{"journal-title":"Hands-on machine learning for algorithmic trading design and implement investment strategies based on smart algorithms that learn from data using Python","year":"2018","author":"jansen","key":"ref7"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CISS.2017.7926112"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CoDIT49905.2020.9263850"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-017-3324-x"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.enpol.2012.12.004"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ACIT53391.2021.9677302"}],"event":{"name":"2023 International Conference on Control, Automation and Diagnosis (ICCAD)","start":{"date-parts":[[2023,5,10]]},"location":"Rome, Italy","end":{"date-parts":[[2023,5,12]]}},"container-title":["2023 International Conference on Control, Automation and Diagnosis (ICCAD)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10151847\/10152298\/10152457.pdf?arnumber=10152457","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,7,10]],"date-time":"2023-07-10T17:50:59Z","timestamp":1689011459000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10152457\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,5,10]]},"references-count":16,"URL":"https:\/\/doi.org\/10.1109\/iccad57653.2023.10152457","relation":{},"subject":[],"published":{"date-parts":[[2023,5,10]]}}}