Journal
COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE
Volume 2016, Issue -, Pages -Publisher
HINDAWI LTD
DOI: 10.1155/2016/3868519
Keywords
-
Ask authors/readers for more resources
The presented paper compares forecast of drought indices based on two different models of artificial neural networks. The first model is based on feed forward multilayer perceptron, sANN, and the second one is the integrated neural network model, hANN. The analyzed drought indices are the standardized precipitation index (SPI) and the standardized precipitation evaporation index (SPEI) andwere derived for the period of 1948-2002 on two US catchments. The meteorological and hydrological data were obtained from MOPEX experiment. The training of both neural network models was made by the adaptive version of differential evolution, JADE. The comparison of models was based on six model performance measures. The results of drought indices forecast, explained by the values of four model performance indices, show that the integrated neural network model was superior to the feed forward multilayer perceptron with one hidden layer of neurons.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available