Short term load forecast using fuzzy logic and wavelet transform integrated generalized neural network

Application of Artificial Neural Networks (ANNs) for electrical load forecasting has been proposed in the literature. ANNs have some inherent drawbacks and limitations, such as difficulty in deciding the structure of ANN, selection of type of neuron, large training time, sticking to local minima, etc. To overcome the drawbacks of ANN, a Generalized Neural Network (GNN) has been proposed in the past. An algorithm that integrates wavelet transform, adaptive genetic algorithm and fuzzy system with GNN is described and applied to the short term week day electrical load forecasting problem. Performance of the proposed algorithm is compared with other GNN variants on the basis of prediction error. 2014 Elsevier Ltd. All rights reserved.