基于MATLAB的神经网络在湖泊富营养化评价中的应用

Application of neural network based on MATLAB toolbox to the evaluation of lake eutrophication

以MATLAB为工具,建立评价湖泊水体富营养化状态的BP神经网络模型,应用此模型对我国9个湖泊富营养化程度进行评价。将此评价结果与用分级评分法、模糊数学法、Fuzzy Grey决策法的评价结果进行比较分析,得出较一致的结论。同时表明用MATLAB构建神经网络简洁、高效,具有更好的通用性和实用性。

A BP neural network model based on MATLAB toolbox is established to assess the eutrophication of lakes. It is applied to the evaluation of 9 lakes in China. The results fit well with those concluded by the grading evaluation method, the fuzzy mathematics method, and the fuzzy-Grey decision-making method. It shows that this simple, clear, and efficient model can be generally and practically used.