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基于优化BP网络的工厂化水产养殖水质预测模型的实现
Prediction model and realization for water quality in an intensive aquaculture based on L-M BP neural network
【摘要】 在分析影响工厂化水产养殖水质因素的基础上,利用BP神经网络良好的非线性映射特性,建立了工厂化水产养殖水质预测模型,并利用MATLAB神经网络工具箱编程实现。训练结果表明:用L-M BP网络预测工厂化水产养殖水质,收敛速度快,预测精度高,能有效地预测水产养殖中的水质状况。
【Abstract】 A modeling method of prediction for water quality in an intensive aquaculture was designed using better nonlinear approaching ability of neural network.This model was realized by programming with tool box of MATLAB neural network.The training results showed that L-M neural network was convergent quickly and provided precise prediction.It was an efficient for predicting fishery water quality and had practical means to regulate water quality and to realize industrialized aquaculture.
【关键词】 神经网络;
MATLAB;
预测模型;
工厂化水产养殖;
【Key words】 neural network; MATLAB; prediction model; industrialized aquaculture;
【Key words】 neural network; MATLAB; prediction model; industrialized aquaculture;
- 【文献出处】 大连水产学院学报 ,Journal of Dalian Fisheries University , 编辑部邮箱 ,2008年03期
- 【分类号】S951.2
- 【被引频次】20
- 【下载频次】284