کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
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384745 | 660854 | 2009 | 5 صفحه PDF | دانلود رایگان |
This paper investigates the effectiveness of the genetic algorithm (GA) evolved neural network for rainfall–runoff forecasting and its application to predict the runoff in a catchment located in a semi-arid climate in Morocco. To predict the runoff at given moment, the input variables are the rainfall and the runoff values observed on the previous time period. Our methodology adopts a real coded GA strategy and hybrid with a back-propagation (BP) algorithm. The genetic operators are carefully designed to optimize the neural network, avoiding premature convergence and permutation problems. To evaluate the performance of the genetic algorithm-based neural network, BP neural network is also involved for a comparison purpose. The results showed that the GA-based neural network model gives superior predictions. The well-trained neural network can be used as a useful tool for runoff forecasting.
Journal: Expert Systems with Applications - Volume 36, Issue 3, Part 1, April 2009, Pages 4523–4527