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Solar irradiance modeling is usually a time\u2010dependent dynamic model. As a new kind of recurrent neural network, echo state network (ESN) shows excellent performance in the field of time series prediction. However, the memory length of classical ESN is fixed and finite, which makes it hard to map sufficient features of solar irradiance with long\u2010range dependency. Therefore, a novel deep echo state network with variable memory pattern (VMP\u2010DESN) is proposed in this brief. VMP\u2010DESN consists of multiple connected reservoirs in series, and there exist different types of memory modes in VMP\u2010DESN. To remember more input history information in the states, the time delay links are added in each reservoir and between every two reservoirs. The VMP\u2010DESN is more flexible to deal with different input signals due to its variable memory modes in the reservoir states. Additionally, the effect of different memory patterns on the VMP\u2010DESN performance is discussed in detail, including the antidisturbance ability, memory capacity, and prediction accuracy. Finally, the effectiveness of VMP\u2010DESN is evaluated by predicting the real solar irradiance task.<\/jats:p>","DOI":"10.1155\/2022\/8506312","type":"journal-article","created":{"date-parts":[[2022,10,26]],"date-time":"2022-10-26T23:05:09Z","timestamp":1666825509000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Deep Echo State Network with Variable Memory Pattern for Solar Irradiance Prediction"],"prefix":"10.1155","volume":"2022","author":[{"given":"Qian","family":"Li","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tao","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiangang","family":"Ouyang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3937-5235","authenticated-orcid":false,"given":"Dayong","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8630-431X","authenticated-orcid":false,"given":"Zhijun","family":"Guo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2022,10,26]]},"reference":[{"key":"e_1_2_9_1_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.renene.2016.12.095"},{"key":"e_1_2_9_2_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.solener.2018.01.007"},{"key":"e_1_2_9_3_2","doi-asserted-by":"publisher","DOI":"10.1109\/tii.2016.2634624"},{"key":"e_1_2_9_4_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2021.117061"},{"key":"e_1_2_9_5_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.renene.2016.01.020"},{"key":"e_1_2_9_6_2","doi-asserted-by":"publisher","DOI":"10.1109\/tsg.2014.2377178"},{"key":"e_1_2_9_7_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2021.117193"},{"key":"e_1_2_9_8_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jclepro.2015.04.041"},{"key":"e_1_2_9_9_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2005.12.138"},{"key":"e_1_2_9_10_2","doi-asserted-by":"publisher","DOI":"10.1126\/science.1091277"},{"key":"e_1_2_9_11_2","doi-asserted-by":"publisher","DOI":"10.1109\/tnn.2010.2089641"},{"key":"e_1_2_9_12_2","doi-asserted-by":"publisher","DOI":"10.1109\/tcyb.2018.2825253"},{"key":"e_1_2_9_13_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.107007"},{"key":"e_1_2_9_14_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2020.114791"},{"key":"e_1_2_9_15_2","doi-asserted-by":"publisher","DOI":"10.1007\/s12559-017-9468-2"},{"key":"e_1_2_9_16_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2018.09.057"},{"key":"e_1_2_9_17_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.amc.2021.126324"},{"key":"e_1_2_9_18_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2017.09.083"},{"key":"e_1_2_9_19_2","doi-asserted-by":"publisher","DOI":"10.1109\/tie.2013.2253072"},{"key":"e_1_2_9_20_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2018.08.002"},{"key":"e_1_2_9_21_2","doi-asserted-by":"publisher","DOI":"10.1109\/tcyb.2016.2533545"},{"key":"e_1_2_9_22_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2019.09.049"},{"key":"e_1_2_9_23_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2020.106481"},{"key":"e_1_2_9_24_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2007.04.016"},{"key":"e_1_2_9_25_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2016.07.065"},{"key":"e_1_2_9_26_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.chemolab.2020.104062"},{"key":"e_1_2_9_27_2","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2021.3098866"},{"key":"e_1_2_9_28_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jclepro.2020.121151"},{"key":"e_1_2_9_29_2","doi-asserted-by":"publisher","DOI":"10.1109\/tii.2020.2987096"},{"key":"e_1_2_9_30_2","doi-asserted-by":"crossref","unstructured":"WyffelsF. 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