Artificial neural networks for electricity consumption forecasting considering climatic factors
Document Type
Conference Proceeding
Publication Date
12-1-2010
Publication Title
Proc. of the 11th WSEAS Int. Conf. on Neural Networks, NN '10, Proceedings of the 11th WSEAS Int. Conf. on Evolutionary Computing, EC '10, Proc. of the 11th WSEAS Int. Conf. on Fuzzy Systems, FS '10
Abstract
This work develops Artificial Neural Networks (ANN) models applied to predict the consumption forecasting considering climatic factors. It is intended to verify the influence of climatic factors on the electricity consumption forecasting through the ANN. The case study is applied in the Campinas city, Brazil. This work used Perceptron and Backpropagation ANN models. The specific goal is comparisons the performance of neural networks as an alternative to traditional forecasting methods. In this work were observed that despite direct or indirect influence of climatic factors on electricity consumption, a good prediction can be obtained using ANN without climatic factors.
First Page
293
Last Page
298
ISBN
9789604741953
Recommended Citation
Moya Chaves, Francisco David, "Artificial neural networks for electricity consumption forecasting considering climatic factors" (2010). Scopus Unisalle. 640.
https://ciencia.lasalle.edu.co/scopus_unisalle/640
Identifier
SCOPUS_ID:79952641857