{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,8]],"date-time":"2026-04-08T00:43:07Z","timestamp":1775608987438,"version":"3.50.1"},"reference-count":23,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2016,9,16]],"date-time":"2016-09-16T00:00:00Z","timestamp":1473984000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004608","name":"Natural Science Foundation of Jiangsu Province","doi-asserted-by":"publisher","award":["BK20160355"],"award-info":[{"award-number":["BK20160355"]}],"id":[{"id":"10.13039\/501100004608","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Science and Technology Project of Ministry of Housing and Urban-Rural Development","award":["2016-K1-019, 2014-K1-040"],"award-info":[{"award-number":["2016-K1-019, 2014-K1-040"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>Due to the high cost of photovoltaic (PV) modules, an accurate performance estimation method is significantly valuable for studying the electrical characteristics of PV generation systems. Conventional analytical PV models are usually composed by nonlinear exponential functions and a good number of unknown parameters must be identified before using. In this paper, an adaptive-network-based fuzzy inference system (ANFIS) based modeling method is proposed to predict the current-voltage characteristics of PV modules. The effectiveness of the proposed modeling method is evaluated through comparison with Villalva\u2019s model, radial basis function neural networks (RBFNN) based model and support vector regression (SVR) based model. Simulation and experimental results confirm both the feasibility and the effectiveness of the proposed method.<\/jats:p>","DOI":"10.3390\/sym8090096","type":"journal-article","created":{"date-parts":[[2016,9,19]],"date-time":"2016-09-19T10:07:43Z","timestamp":1474279663000},"page":"96","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["ANFIS-Based Modeling for Photovoltaic Characteristics Estimation"],"prefix":"10.3390","volume":"8","author":[{"given":"Ziqiang","family":"Bi","sequence":"first","affiliation":[{"name":"School of Electronic and Information Engineering, Suzhou University of Science and Technology, Suzhou 215011, China"},{"name":"Department of Computer Science and Software Engineering, Xi\u2019an Jiaotong-Liverpool University, Suzhou 215123, China"}]},{"given":"Jieming","family":"Ma","sequence":"additional","affiliation":[{"name":"School of Electronic and Information Engineering, Suzhou University of Science and Technology, Suzhou 215011, China"},{"name":"Department of Computer Science and Software Engineering, Xi\u2019an Jiaotong-Liverpool University, Suzhou 215123, China"}]},{"given":"Xinyu","family":"Pan","sequence":"additional","affiliation":[{"name":"School of Electronic and Information Engineering, Suzhou University of Science and Technology, Suzhou 215011, China"}]},{"given":"Jian","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Electronic and Information Engineering, Suzhou University of Science and Technology, Suzhou 215011, China"}]},{"given":"Yu","family":"Shi","sequence":"additional","affiliation":[{"name":"School of Electronic and Information Engineering, Suzhou University of Science and Technology, Suzhou 215011, China"}]}],"member":"1968","published-online":{"date-parts":[[2016,9,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"500","DOI":"10.1016\/j.apenergy.2015.05.035","article-title":"Cell modelling and model parameters estimation techniques for photovoltaic simulator application: A review","volume":"154","author":"Chin","year":"2015","journal-title":"Appl. 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