{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T02:56:57Z","timestamp":1773716217846,"version":"3.50.1"},"reference-count":53,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"name":"Research Fund of Guangdong-Hong Kong-Macao Joint Laboratory for Intelligent Micro-Nano Optoelectronic Technology","award":["2020B1212030010"],"award-info":[{"award-number":["2020B1212030010"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2023]]},"DOI":"10.1109\/access.2023.3259424","type":"journal-article","created":{"date-parts":[[2023,3,20]],"date-time":"2023-03-20T17:55:50Z","timestamp":1679334950000},"page":"32308-32318","source":"Crossref","is-referenced-by-count":12,"title":["A Novel Convolutional Neural Networks for Stock Trading Based on DDQN Algorithm"],"prefix":"10.1109","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3399-848X","authenticated-orcid":false,"given":"Kai","family":"Cui","sequence":"first","affiliation":[{"name":"School of Computer Science and Engineering, Macau University of Science and Technology, Macau, China"}]},{"given":"Ruizhe","family":"Hao","sequence":"additional","affiliation":[{"name":"Military Science Information Research Center, Academy of Military Science, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3992-9744","authenticated-orcid":false,"given":"Yuling","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Macau University of Science and Technology, Macau, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6768-1483","authenticated-orcid":false,"given":"Jianqing","family":"Li","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Macau University of Science and Technology, Macau, China"}]},{"given":"Yunlin","family":"Song","sequence":"additional","affiliation":[{"name":"School of Business, Macau University of Science and Technology, Macau, China"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ipm.2023.103293"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.procs.2020.03.328"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-33-6173-7_22"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2022.109428"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1007\/s12652-020-01839-w"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcp.2019.109071"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/3065386"},{"key":"ref8","article-title":"Very deep convolutional networks for large-scale image recognition","author":"Simonyan","year":"2014","journal-title":"arXiv:1409.1556"},{"key":"ref9","article-title":"Faster R-CNN: Towards real-time object detection with region proposal networks","author":"Ren","year":"2015","journal-title":"arXiv:1506.01497"},{"key":"ref10","article-title":"Deep residual learning for image recognition","author":"He","year":"2015","journal-title":"arXiv:1512.03385"},{"key":"ref11","article-title":"You only look once: Unified, real-time object detection","author":"Redmon","year":"2015","journal-title":"arXiv:1506.02640"},{"key":"ref12","article-title":"YOLO9000: Better, faster, stronger","author":"Redmon","year":"2016","journal-title":"arXiv:1612.08242"},{"key":"ref13","article-title":"YOLOv3: An incremental improvement","author":"Redmon","year":"2018","journal-title":"arXiv:1804.02767"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.2004.10934"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"ref16","article-title":"Going deeper with convolutions","author":"Szegedy","year":"2014","journal-title":"arXiv:1409.4842"},{"key":"ref17","article-title":"Rethinking the inception architecture for computer vision","author":"Szegedy","year":"2015","journal-title":"arXiv:1512.00567"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v31i1.11231"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.3390\/app10010101"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1002\/(sici)1099-131x(199604)15:3<203::aid-for619>3.0.co;2-y"},{"key":"ref21","article-title":"Multi-scale convolutional neural networks for time series classification","author":"Cui","year":"2016","journal-title":"arXiv:1603.06995"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-021-06290-2"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2023.119527"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2020\/628"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2022.07.016"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.3390\/math8101640"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2021.114800"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2021.114632"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1994.6.2.215"},{"key":"ref30","first-page":"936","article-title":"Enhancing Q-learning for optimal asset allocation","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"10","author":"Neuneier"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.2139\/ssrn.2617630"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/cec.2007.4424475"},{"key":"ref33","first-page":"917","article-title":"Reinforcement learning for trading","volume-title":"Proc. 11th Int. Conf. Neural Inf. Process. Syst.","author":"Moody"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/72.935097"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/cifer.2003.1196283"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1145\/2464576.2480773"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1007\/s10614-015-9490-y"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/iscid.2017.210"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1007\/s11280-018-0534-9"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/icsess47205.2019.9040728"},{"key":"ref41","article-title":"Capturing financial markets to apply deep reinforcement learning","author":"Chakraborty","year":"2019","journal-title":"arXiv:1907.04373"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.2139\/ssrn.3522712"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1007\/s00607-019-00773-w"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2020.05.066"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2021.107320"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2022.116523"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2016.2522401"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2021.107952"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.3905\/jfds.2020.1.030"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/access.2019.2932789"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1155\/2022\/4698656"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-90639-9_74"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/tnn.1998.712192"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/10005208\/10077346.pdf?arnumber=10077346","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,2,13]],"date-time":"2024-02-13T17:50:43Z","timestamp":1707846643000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10077346\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"references-count":53,"URL":"https:\/\/doi.org\/10.1109\/access.2023.3259424","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023]]}}}