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This paper proposes a new method for the prediction of daily maximum electric load by using a reccurent neural network. Although algorithms like back-propagation are usually utilized in learning of recurrent neural networks, there are two serious problems, which one is that learning algorithm is inadequate to achieve optimum weight vector, i.e., local minimum problem, the other is that there is no method of settling structure of network. Proposed method can overcome these two problems by applying genetic algorithm to learning of recurrent neural networks. Two types of crossover operators are newly introduced into genetic algorithm for the optimization of the network structures. Therefore the number of hidden units is automatically fixed and local minimum can be avoided. Computational experiments show that the proposed method can produce recurrent neural networks with high abilities of prediction.

Prediction of Daily Maximum Electric Load by a Recurrent Neural Network Using Genetic Algorithm