Optimizing neural networks using faster, more accurate genetic search
Proceedings of the third international conference on Genetic algorithms
Introduction to the theory of neural computation
Introduction to the theory of neural computation
Learning internal representations by error propagation
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
Creating artificial neural networks that generalize
Neural Networks
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Neural Networks in Computer Intelligence
Neural Networks in Computer Intelligence
Optimizing Neural Networks Using FasterMore Accurate Genetic Search
Proceedings of the 3rd International Conference on Genetic Algorithms
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To increase the efficiency of Artificial Neural Network in a relatively short time is a very important issue. Genetic algorithms are a class of optimization procedures which are good at exploring a large and complex space in an intelligent way. Genetic algorithms have been used for neural networks in two main ways: to optimize the network architecture and to train the weights of a fixed architecture. In this paper, a Neural-Genetic based technique is proposed to Increase the efficiency of neural network. Compared with ordinary weighted algorithm, the algorithm proposed in this paper achieved high predicting accuracy.