1.School of Information Engineering,Dalian Ocean University,Dalian 116023,China;2.Vocational and Technical College,Dalian Ocean University,Dalian 116300,China;3.School of Science,Dalian Ocean University,Dalian 116023,China
Abstract: The prediction of dissolved oxygen(DO)level is complicated in aquaculture ponds as a complex system with multi-variables,nonlinearity and long-time lag.In this study,GA-LM,a hybrid neural network model combining Levenberg Marquardt(LM)algorithm and Genetic Algorithm(GA)was developed for DO level predicting in an aquaculture pond at Dalian,China.The The comparison of performance of GA-LM with the conventional Back -Propagation(BP)algorithm revealed that the predicted DO values using GA-LM model are in good agreement with the measured data,indicating that the model is capable of predicting DO accurately and rapidly.
缪新颖, 葛廷友, 高, 王建彬. 基于神经网络和遗传算法的池塘溶解氧预测模型[J]. 大连海洋大学学报, 2011, 26(3): 264-267.
MIAO Xin-ying, GE Ting-you, GAO Hui, WANG Jian-bin. A prediction model for dissolved oxygen level in a fish pond based on combination of neural network and genetic algorithm. Journal of Dalian Ocean University, 2011, 26(3): 264-267.
2011, Vol. 26 
