Evolving neural network using real coded genetic algorithm for permeability estimation of the reservoir
作者： Rasoul Irani , Reza Nasimi
DOI: 10.1016/J.ESWA.2011.02.046
关键词:
摘要: In this work we investigate how artificial neural network (ANN) evolution with genetic algorithm (GA) improves the reliability and predictability of network. This strategy is applied to predict permeability Mansuri Bangestan reservoir located in Ahwaz, Iran utilizing available geophysical well log data. Our methodology utilizes a hybrid algorithm-neural (GA-ANN). The proposed combines local searching ability gradient-based back-propagation (BP) global algorithms. Genetic algorithms are used decide initial weights gradient decent methods so that all can be searched intelligently. operators parameters carefully designed set avoiding premature convergence permutation problems. For an evaluation purpose, performance generalization capabilities GA-ANN compared those models developed common technique BP. results demonstrate algorithm-based outperforms descent-based
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