A Combined Genetic Algorithm and Orthogonal Transformation for Designing Feedforward Neural Networks

In this paper, a hybrid algorithm is proposed for designing feedforward neural networks. A genetic algorithm is used to tune the connections and parameters between the input layer and the hidden layer, and orthogonal transformation is applied to tune the connections and parameters between the hidden layer and the output layer. In this way, both the structure and parameters of a neural network can be optimized efficiently. Simulations are presented to demonstrate the effectiveness of the proposed approach.