{“status”:“ok”,“message type”:“work”,“message version”:“1.0.0”,“message”:{“indexed”:{“date parts”:[[2024,4,10],“date time”:“2024-04-10T09:53:23Z”,“timestamp”:1712742803925},“reference count”:0,“publisher”:“IGI Global”,“issue”:“2”,“license”:[{“start”:{“date parts”:[[2021,4,1]],“date time”:“2021-04-01T00:00:00Z”,“timestamp”:1617235200000},“content-version”:“vor”,“delay-in-days”:0,“URL”:“http://\/creativecommons.org\/licenses\/by\/3.0\/dode.en_US”},{“start”:{“date-parts”:[[2021,4,1]],“date-time”:“2021-04-01T00:00:00Z”,“timestamp”:1617235200000},“content-version”:“am”,“delay-in-days”:“0,”URL“http://creativecommons-org\/licenses\/by\/3.0\/dote.en_US“},{“start”:{“date-parts”:[[2021,4,1]],“date-time”:“2021-04-01T00:00:00Z”,“timestamp”:1617235200000},“content-version”:“tdm”,“delay-in-days”:0,“URL”:“http://\/creativecommons.org\/licenses\/by\/3.0\/dote.en_US”}],“content-domain”:{“domain”:[],“crossmark-restriction”:false},”short-container-title“:[],”published-print“:{”date parts“:[[2021,4]]},”抽象“:”随着电力市场重组的热潮,风力发电已成为智能电网发电的关键因素之一,近年来势头强劲。准确的风电功率预测对于降低风电的备用容量、提高风电的渗透性、电力系统的稳定性和经济运行具有重要意义。时间序列模型广泛应用于风力发电预测。ARIMA模型中的模型估计通常是通过最大化对数似然函数来完成的,它需要对输入值的任何变化进行重新估计。这会降低ARIMA模型的性能。在本文中,ARIMA模型的模型估计是使用最新的进化算法(即动态粒子群优化[DPSO])完成的。DPSO算法的使用消除了输入值发生任何变化时对模型系数进行重新估计的需要,并且提高了ARIMA模型的性能。将提出的DPSO-ARIMA模型与现有模型的性能进行了比较<\/jats:p>“,”DOI“:”10.4018\/ijcini.20210401.oa9“,”type“:”journal-article“,”created“:{”date-parts“:[[2020,12,14]],”date-time“:”2020-12-14T15:21:49Z“,”timestamp“:1607959309000},”page“:“111-138”,“source”:“Crossref”,“is-referenced-by-count”:10,“title”:[“基于混合自回归综合移动平均模型和动态粒子群优化的短期风电预测“],前缀:“10.4018”,卷:“15”,作者:[{“given”:“Pavan Kumar”,“family”:“Singh”,“sequence”:“first”,“affiliation”:[{name”:“MNNIT,Allahabad,India”}]},{given:“Nitin”,“家族”:“辛格”,“序列”:“additional”,“affiliation“:[{”name“:”MNNIT,Allahabad,India“}]},{”given“:”Richa“,”family“:”Negi“,”sequence“:”additional“,”affiliance“:[[{“name”:”MNNIT,Allashabad,印度“}]],“member”:“2432”,“container-title”:[“国际认知信息学和自然智能杂志”],“original-title“:[],”language“:”en“,”link“:[}”URL“:”https:\/\/www.igi-global.com/viewtitle.aspx?TitleId=268854“,”content-type“:”unspecified“,”content-version“:”vor“,”intended-application“:”similarity-checking“}],”deposed“:{”date-parts“:[2022,5,6]],”date-time“:“2022-05-06T05:55:59Z”,”timestamp“:1651816559000},”score“:1,”resource“:{“primary”:{“URL”:“http://services.igi-global.com\\resolvedoi\/resolve.aspx?doi=10.4 018\/IJCINI.20210401.oa9“}},“subtitle”:[“”],“shorttitle”:[],“issued”:{“date-parts”:[[2021,4]},“references-count”:0,“journal-issue”:{“issue”:“2”},”URL“:”http://\/dx.doi.org\/10.4018\/ijcini.20210401.oa9“,”relationship“:{},‘ISSN’:[“1557-3958”,“1557-39”],‘ISSN-type’:[{“value”:“1557-”3966“]58“,”type“:”print“},”{“value”:“1557-3966”,“type”:”electronic“}],“subject”:[],“published”:{“日期部分”:[[2021,4]]}}