RbfCon: Construct Radial Basis Function Neural Networks with Grammatical Evolution
Radial basis function networks are considered a machine learning tool that can be applied on a wide series of classification and regression problems proposed in various research topics of the modern world. However, in many cases, the initial training method used to fit the parameters of these models...
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| Format: | Article |
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MDPI AG
2024-12-01
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| Series: | Software |
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| Online Access: | https://www.mdpi.com/2674-113X/3/4/27 |
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| author | Ioannis G. Tsoulos Ioannis Varvaras Vasileios Charilogis |
| author_facet | Ioannis G. Tsoulos Ioannis Varvaras Vasileios Charilogis |
| author_sort | Ioannis G. Tsoulos |
| collection | DOAJ |
| description | Radial basis function networks are considered a machine learning tool that can be applied on a wide series of classification and regression problems proposed in various research topics of the modern world. 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. |
| format | Article |
| id | doaj-art-6116ec9d836c4255b1ff91fe3d429e7c |
| institution | DOAJ |
| issn | 2674-113X |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Software |
| spelling | doaj-art-6116ec9d836c4255b1ff91fe3d429e7c2025-08-20T02:43:49ZengMDPI AGSoftware2674-113X2024-12-013454956810.3390/software3040027RbfCon: Construct Radial Basis Function Neural Networks with Grammatical EvolutionIoannis G. Tsoulos0Ioannis Varvaras1Vasileios Charilogis2Department of Informatics and Telecommunications, University of Ioannina, 45110 Ioannina, GreeceDepartment of Informatics and Telecommunications, University of Ioannina, 45110 Ioannina, GreeceDepartment of Informatics and Telecommunications, University of Ioannina, 45110 Ioannina, GreeceRadial basis function networks are considered a machine learning tool that can be applied on a wide series of classification and regression problems proposed in various research topics of the modern world. 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.https://www.mdpi.com/2674-113X/3/4/27neural networksgenetic programmingGrammatical Evolutionevolutionary algorithms |
| spellingShingle | Ioannis G. Tsoulos Ioannis Varvaras Vasileios Charilogis RbfCon: Construct Radial Basis Function Neural Networks with Grammatical Evolution Software neural networks genetic programming Grammatical Evolution evolutionary algorithms |
| title | RbfCon: Construct Radial Basis Function Neural Networks with Grammatical Evolution |
| title_full | RbfCon: Construct Radial Basis Function Neural Networks with Grammatical Evolution |
| title_fullStr | RbfCon: Construct Radial Basis Function Neural Networks with Grammatical Evolution |
| title_full_unstemmed | RbfCon: Construct Radial Basis Function Neural Networks with Grammatical Evolution |
| title_short | RbfCon: Construct Radial Basis Function Neural Networks with Grammatical Evolution |
| title_sort | rbfcon construct radial basis function neural networks with grammatical evolution |
| topic | neural networks genetic programming Grammatical Evolution evolutionary algorithms |
| url | https://www.mdpi.com/2674-113X/3/4/27 |
| work_keys_str_mv | AT ioannisgtsoulos rbfconconstructradialbasisfunctionneuralnetworkswithgrammaticalevolution AT ioannisvarvaras rbfconconstructradialbasisfunctionneuralnetworkswithgrammaticalevolution AT vasileioscharilogis rbfconconstructradialbasisfunctionneuralnetworkswithgrammaticalevolution |