Abstract:
Precipitation is viewed as a complex phenomenon that influences the efficiency of the agricultural season. In this paper, an ensemble of neural networks has been created ...Show MoreMetadata
Abstract:
Precipitation is viewed as a complex phenomenon that influences the efficiency of the agricultural season. In this paper, an ensemble of neural networks has been created and optimized to estimate monthly rainfall for Innisfail, Australia. The proposed ensemble utilizes single neural networks as components and combines them using a neural network fusion method. A novel ensemble components selection approach has been proposed and deployed. Ensemble components were selected based on a hybrid Genetic Algorithm (GA) that combines standard GA with particle swarm optimization algorithm. Various statistical measurements were calculated to assess the accuracy of the proposed ensembles against single neural networks, climatology and ensembles generated through an alternative selection approach. A better performance was obtained with the proposed ensembles when compared to alternative models.
Published in: 2018 IEEE Congress on Evolutionary Computation (CEC)
Date of Conference: 08-13 July 2018
Date Added to IEEE Xplore: 04 October 2018
ISBN Information: