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The improvement of the performance of the fuzzy rule-based model quantified in terms of Root Mean Squared Error is 20.86%, 51.91%, 62.28%, 65.10%, and 71.92% in comparison with that of the Ridge model, Lasso model, and a family of support vector machine model with different kernel functions, including linear kernel (SVM-linear), radial basis function (SVM-BRF), polynomial kernel (SVM-polynomial) respectively, on the electromagnetic field testing data, and 37.42%, 55.16%, 58.79%, 59.28%, 64.27% lower than that of the Ridge model, Lasso model, SVM-linear model, SVM-BRF model and SVM-polynomial model on the power frequency electric field testing data.<\/jats:p>","DOI":"10.1007\/s40747-024-01534-9","type":"journal-article","created":{"date-parts":[[2024,7,8]],"date-time":"2024-07-08T13:02:27Z","timestamp":1720443747000},"page":"7199-7211","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["A granularity data method for power frequency electric and electromagnetic fields forecasting based on T\u2013S fuzzy model"],"prefix":"10.1007","volume":"10","author":[{"given":"Peng","family":"Nie","sequence":"first","affiliation":[]},{"given":"Qiang","family":"Yu","sequence":"additional","affiliation":[]},{"given":"Zhenkun","family":"Li","sequence":"additional","affiliation":[]},{"given":"Xiguo","family":"Yuan","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,7,8]]},"reference":[{"key":"1534_CR1","doi-asserted-by":"crossref","DOI":"10.1016\/j.envres.2021.111993","volume":"204","author":"AT Amoon","year":"2022","unstructured":"Amoon AT, Swanson J, Magnani C, Kheifets L (2022) Pooled analysis of recent studies of magnetic fields and childhood leukemia. 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