Name
Abstract | ||
|---|---|---|
A novel hybrid method is proposed for neural network training. The method consists of two phases: in the first phase the bounds for the neural network parameters are estimated using a genetic algorithm that uses intervals as chromosomes. In the second phase a genetic algorithm is used to train the neural network inside the bounding box located by the first phase. The proposed method is tested on a series of well-known datasets from the relevant literature and the results are reported. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1007/s11063-020-10347-z | NEURAL PROCESSING LETTERS |
Keywords | DocType | Volume |
Neural networks, Genetic algorithms, Intervals, Optimization | Journal | 52 |
Issue | ISSN | Citations |
3 | 1370-4621 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nikolaos P. Anastasopoulos | 1 | 0 | 0.34 |
| Ioannis G. Tsoulos | 2 | 163 | 16.58 |
| Evaggelos C. Karvounis | 3 | 17 | 3.94 |
| Alexandros T. Tzallas | 4 | 225 | 27.88 |