Título: Neural Network Models for Climate Forecasting based on Reanalysis Data
Autores: Anochi, Juliana Aparecida; Silva, José Demisio Simões da
Resumo: In this work a neural network model for climate forecasting is presented. The model is built by training a neural network with available reanalysis data. In order to assess the model, the development methodology considers the use of data reduction strategies that eliminate data redundancy thus reducing the complexity of the models. The results presented in this paper considered the use of Rough Sets Theory principles in extracting relevant information from the available data to achieve the reduction of redundancy among the variables used for forecasting purposes. The paper presents results of climate prediction made with the use of the neural network based model.
Palavras-chave: Climate Forecasting; Rough Sets Theory; Artificial Neural Networks; Artificial Intelligence
Código DOI: 10.21528/CBIC2011-19.5
Artigo em pdf: st_19.5.pdf
Arquivo BibTex: st_19.5.bib