Adapting the Parameters of RBF Networks Using Grammatical Evolution
Radial basis function networks are widely used in a multitude of applications in various scientific areas in both classification and data fitting problems. These networks deal with the above problems by adjusting their parameters through various optimization techniques. However, an important issue t...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-12-01
|
| Series: | AI |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2673-2688/4/4/54 |
| _version_ | 1827575888414244864 |
|---|---|
| author | Ioannis G. Tsoulos Alexandros Tzallas Evangelos Karvounis |
| author_facet | Ioannis G. Tsoulos Alexandros Tzallas Evangelos Karvounis |
| author_sort | Ioannis G. Tsoulos |
| collection | DOAJ |
| description | Radial basis function networks are widely used in a multitude of applications in various scientific areas in both classification and data fitting problems. These networks deal with the above problems by adjusting their parameters through various optimization techniques. However, an important issue to address is the need to locate a satisfactory interval for the parameters of a network before adjusting these parameters. This paper proposes a two-stage method. In the first stage, via the incorporation of grammatical evolution, rules are generated to create the optimal value interval of the network parameters. During the second stage of the technique, the mentioned parameters are fine-tuned with a genetic algorithm. The current work was tested on a number of datasets from the recent literature and found to reduce the classification or data fitting error by over 40% on most datasets. In addition, the proposed method appears in the experiments to be robust, as the fluctuation of the number of network parameters does not significantly affect its performance. |
| first_indexed | 2024-03-08T21:03:20Z |
| format | Article |
| id | doaj.art-33ded518c502443fa474a8dc25b59e37 |
| institution | Directory Open Access Journal |
| issn | 2673-2688 |
| language | English |
| last_indexed | 2024-03-08T21:03:20Z |
| publishDate | 2023-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | AI |
| spelling | doaj.art-33ded518c502443fa474a8dc25b59e372023-12-22T13:46:58ZengMDPI AGAI2673-26882023-12-01441059107810.3390/ai4040054Adapting the Parameters of RBF Networks Using Grammatical EvolutionIoannis G. Tsoulos0Alexandros Tzallas1Evangelos Karvounis2Department 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 widely used in a multitude of applications in various scientific areas in both classification and data fitting problems. These networks deal with the above problems by adjusting their parameters through various optimization techniques. However, an important issue to address is the need to locate a satisfactory interval for the parameters of a network before adjusting these parameters. This paper proposes a two-stage method. In the first stage, via the incorporation of grammatical evolution, rules are generated to create the optimal value interval of the network parameters. During the second stage of the technique, the mentioned parameters are fine-tuned with a genetic algorithm. The current work was tested on a number of datasets from the recent literature and found to reduce the classification or data fitting error by over 40% on most datasets. In addition, the proposed method appears in the experiments to be robust, as the fluctuation of the number of network parameters does not significantly affect its performance.https://www.mdpi.com/2673-2688/4/4/54neural networksgenetic algorithmsgenetic programminggrammatical evolution |
| spellingShingle | Ioannis G. Tsoulos Alexandros Tzallas Evangelos Karvounis Adapting the Parameters of RBF Networks Using Grammatical Evolution AI neural networks genetic algorithms genetic programming grammatical evolution |
| title | Adapting the Parameters of RBF Networks Using Grammatical Evolution |
| title_full | Adapting the Parameters of RBF Networks Using Grammatical Evolution |
| title_fullStr | Adapting the Parameters of RBF Networks Using Grammatical Evolution |
| title_full_unstemmed | Adapting the Parameters of RBF Networks Using Grammatical Evolution |
| title_short | Adapting the Parameters of RBF Networks Using Grammatical Evolution |
| title_sort | adapting the parameters of rbf networks using grammatical evolution |
| topic | neural networks genetic algorithms genetic programming grammatical evolution |
| url | https://www.mdpi.com/2673-2688/4/4/54 |
| work_keys_str_mv | AT ioannisgtsoulos adaptingtheparametersofrbfnetworksusinggrammaticalevolution AT alexandrostzallas adaptingtheparametersofrbfnetworksusinggrammaticalevolution AT evangeloskarvounis adaptingtheparametersofrbfnetworksusinggrammaticalevolution |