基于T-S模糊神经网络的大沽河水质变化特征分析研究

Analysis on Variation Characteristics of Dagu River Based on T-S Fuzzy Neural Network

基于T-S模糊神经网络,利用大沽河2010年-2015年水质监测数据,选取溶解氧、化学需氧量、高锰酸盐指数、氨氮、总氮、总磷对水质具有重要影响的6项指标,建立适用的水质评价模型,对大沽河水质变化特征进行分析。结果显示:上游水质评价结果明显优于中游、下游水质评价结果,网络评价水质等级变化趋势同真实指标数据变化趋势一致。验证结果充分表明了T-S模糊神经网络用于水质变化特征分析是可行、有效的。

Based on T - S fuzzy neural network, the data obtained from 2010 to 2015 was analyzed with six major influencing factors including DO, COD, CODMn, NH3 - N, TN, TP. The water quality evaluation model of T - S fuzzy neural network applied to Dagu River was established, and the variation characteristics of Dagu River were analyzed. Quality assessment results of the upper reaches were better than the middle and lower reaches. The variation trends were consistent between T - S fuzzy neural network and the real data. The validated results indicated that T - S fuzzy neural network was practicable and effective for the analysis on variation characteristics of water quality.