Construction of artificial neural networks using memetic algorithms
The article considers a family of memetic algorithms for constructing artificial neural networks of a special kind. The networks represented by acyclic graphs with a fixed number of input and output neurons are considered as target networks. The memetic algorithm is an evolutionary algorithm for the development of neural networks popuation with iterative partial learning, as well as with the survival, reproduction and mutation of individuals. As the completion of natural selection, the moment is taken when the leader of the population answers correctly all test data from the target set. The considered algorithm allows to automatically find the configuration of neural networks with fewer neurons and connections, as well as having the best characteristics in terms of learning speed.