Application of a Computational Hybrid Model to Estimate and Filling Gaps for Meteorological Time Series
Eluã Ramos Coutinho,
Jonni Guiller Ferreira Madeira,
Robson Mariano da Silva
et al.
Abstract:The present study applies computational intelligence techniques in the development of a hybrid model composed of Artificial Neural Networks (ANNs) and Genetic Algorithms (GAs) (MLP-GA) to estimate and fill in the gaps in the monthly variables of evaporation, maximum temperature and relative humidity to six regions in the state of Rio de Janeiro (RJ), Brazil. The results were evaluated using statistical techniques and compared with results obtained by the Multiple Linear Regression (RLM), Multilayer Perceptron … Show more
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