为准确客观地评价汉江干流汉中段水环境质量状况,利用T-S模糊神经网络模型,对汉江干流汉中段监测点,连续5年的水质监测状况数据进行了分析评价.结果表明,在选取的6个水质监测指标数据下,汉江干流汉中段水质相对较好,但流经城镇段的水质存在恶化的趋势,需要采取措施进行有效的预防保护.提出的T-S模糊神经网络应用于水环境质量评价方法简便可靠,预测精度高,可以在水质评价中进行推广.%In order to evaluate the water environmental quality status accurately and objectively in Hanzhong stretch of Hanjiang mainstream, this paper uses T-S fuzzy neural network model to do analysis and evaluation to the water quality monitoring data got in the monitoring points of Hanzhong stretch of Hanjiang mainstream for five years in a row. The results shows that according to the six selected indicators of water quality monitoring data, the water quality of Hanzhong stretch of Hanjiang mainstream is relatively good, but the water quality of stretch through the town tends to be deteriorated, to which measures should be taken to protect. In this paper, TS fuzzy neural network used in water environmental quality assessment method is simple, reliable, high prediction accuracy, which can promote water quality evaluation.
展开▼
