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However, in many cases, the initial training method used to fit the parameters of these models can produce poor results either due to unstable numerical operations or its inability to effectively locate the lowest value of the error function. The current work proposed a novel method that constructs the architecture of this model and estimates the values for each parameter of the model with the incorporation of Grammatical Evolution. The proposed method was coded in ANSI C++, and the produced software was tested for its effectiveness on a wide series of datasets. The experimental results certified the adequacy of the new method to solve difficult problems, and in the vast majority of cases, the error in the classification or approximation of functions was significantly lower than the case where the original training method was applied.<\/jats:p>","DOI":"10.3390\/software3040027","type":"journal-article","created":{"date-parts":[[2024,12,11]],"date-time":"2024-12-11T12:58:49Z","timestamp":1733921929000},"page":"549-568","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["RbfCon: Construct Radial Basis Function Neural Networks with Grammatical Evolution"],"prefix":"10.3390","volume":"3","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2343-2733","authenticated-orcid":false,"given":"Ioannis G.","family":"Tsoulos","sequence":"first","affiliation":[{"name":"Department of Informatics and Telecommunications, University of Ioannina, 45110 Ioannina, Greece"}]},{"given":"Ioannis","family":"Varvaras","sequence":"additional","affiliation":[{"name":"Department of Informatics and Telecommunications, University of Ioannina, 45110 Ioannina, Greece"}]},{"given":"Vasileios","family":"Charilogis","sequence":"additional","affiliation":[{"name":"Department of Informatics and Telecommunications, University of Ioannina, 45110 Ioannina, Greece"}]}],"member":"1968","published-online":{"date-parts":[[2024,12,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1016\/j.nima.2005.11.139","article-title":"The use of clustering techniques for the classification of high energy physics data, Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers","volume":"559","author":"Mjahed","year":"2006","journal-title":"Detect. 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