{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T06:16:04Z","timestamp":1778220964364,"version":"3.51.4"},"reference-count":32,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41874174"],"award-info":[{"award-number":["41874174"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Postgraduate Research and Practice Innovation Program of Jiangsu Province","award":["KYCX19_1615"],"award-info":[{"award-number":["KYCX19_1615"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2021]]},"DOI":"10.1109\/access.2021.3056713","type":"journal-article","created":{"date-parts":[[2021,2,3]],"date-time":"2021-02-03T22:00:06Z","timestamp":1612389606000},"page":"23660-23671","source":"Crossref","is-referenced-by-count":87,"title":["A Novel Improved Particle Swarm Optimization With Long-Short Term Memory Hybrid Model for Stock Indices Forecast"],"prefix":"10.1109","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1169-5250","authenticated-orcid":false,"given":"Yi","family":"Ji","sequence":"first","affiliation":[{"name":"School of Computer Science and Communication Engineering, Jiangsu University, Jiangsu, Zhenjiang, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6718-7584","authenticated-orcid":false,"given":"Alan Wee-Chung","family":"Liew","sequence":"additional","affiliation":[{"name":"School of Information and Communication Technology, Griffith University, Gold Coast, QLD, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7943-9846","authenticated-orcid":false,"given":"Lixia","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Communication Engineering, Jiangsu University, Jiangsu, Zhenjiang, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref32","article-title":"A comparison of LSTMs and attention mechanisms for forecasting financial time series","author":"hollis","year":"2018","journal-title":"arXiv 1812 07699"},{"key":"ref31","author":"williamson","year":"2020","journal-title":"Annualized Growth Rate and Graphs of the DJIA S&P500 and NASDAQ in the United States Between Any Two Dates"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1007\/s00500-013-1147-y"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/BigData.2015.7364089"},{"key":"ref11","first-page":"1419","article-title":"Stock market&#x2019;s price movement prediction with LSTM neural networks","author":"nelson","year":"2017","journal-title":"Proc Int Joint Conf Neural Netw (IJCNN)"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0180944"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejor.2017.11.054"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-012-1198-5"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2010.11.001"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2019.08.065"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2011.01.037"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.21595\/jve.2017.18594"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TFUZZ.2019.2904920"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2992070"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1080\/02664760903521435"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/ICNN.1995.488968"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.cor.2004.03.016"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1155\/2016\/4907654"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1155\/2019\/1934796"},{"key":"ref5","first-page":"55","article-title":"A comparison between regression, artificial neural networks and support vector machines for predicting stock market index","volume":"4","author":"sheta","year":"2015","journal-title":"Int J Adv Res Artif Intell"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.3233\/JIFS-16209"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2010.08.004"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/S0925-2312(03)00372-2"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.24818\/18423264\/52.4.18.13"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/S0305-0483(01)00026-3"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2806180"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TCBB.2015.2476796"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2019.2943928"},{"key":"ref24","first-page":"155","article-title":"Support vector regression machines","author":"drucker","year":"1996","journal-title":"Proc 9th Int Conf Neural Inf Process Syst (NIPS)"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4757-2440-0"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1016\/S0893-6080(03)00169-2"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/9312710\/09345681.pdf?arnumber=9345681","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,15]],"date-time":"2024-01-15T21:27:15Z","timestamp":1705354035000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9345681\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"references-count":32,"URL":"https:\/\/doi.org\/10.1109\/access.2021.3056713","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]}}}