الفهرس 
Artificial Neural Networks
Differential Evolution Algorithm:Only 14 pages are availabe for public view
 |  | from | 174 |  |  |
| | | from | 174 | | |
Abstract
The artificial neural networks (ANNs) play a pivotal role in systems theory and practice, especially with the enormous capabilities of present-day digital computers. They have been successfully used in many engineering applications of several fields. The learning (or training) of ANNs is the most important subject matter. It is defined as the process of determining the optimal synaptic weights of the ANN that reduce the error between the actual output response and the desired output response through an optimization strategy. There are several optimization algorithms that are used to optimize the ANN such as: back propagation (BP), Hybrid learning algorithms,genetic algorithms (GAs), differential evolution (DE), ant colony optimization (ACO), particle swarm optimization (PSO), and artificial bee colony algorithm (ABC).