基于神经网络模型的水质监测与评价系统

对水环境的监测与评价，可以掌握水质现状及其发展趋势，为水资源的开发利用和管理提供科学依据。水质评价是建立在水质监测基础之上的。首先结合我国水环境监测技术规范与标准，合理地选择监测项目与监测仪器，建立水质监测系统。然后在水质监测所获数据基础上，运用人工神经网络的理论和方法，通过BP网络不断的学习与训练，归纳出评价标准与评价结果间复杂的非线性关系，建立水质评价的BP神经网络模型系统。经实际应用表明，该系统具有很强的学习、联想和容错功能。为水质监测与评价提供了一条新的途径。

A Water Quality Measurement and Evaluation System Based on the Neural Network Model

The monitoring and evaluation of water environment can control the present water quality and the developing tendency of it. It can provide the scientific basis for the exploiting and management of the water resources. The evaluation of water quality is based on the monitoring of water quality. First we should choose reasonable monitoring items and monitoring instruments to set up the water quality monitoring system according to our country's water environment monitoring technical standard. Then we should base on the statistics coming from the water monitoring,apply ANN theory and method, sum up the complex nonlinear relation between the evaluation standard and the evaluation results through the continual study and training of BP neural network, and finally establish the BP neural model network. The practical application shows that this system possesses strong functions of study, association and fault tolerance , and can provide a new way for the monitoring and evaluation of water.