Research on early warning system of water quality safety based on RBF neural network model

Water quality safety early warning system is the key point of ensuring the water resources safety and sustainable use. This paper describes early warning system of water quality safety by using RBF (Radical Basis Function) neural network model. The system consists of four parts: water quality monitoring, early warning of water quality evaluation, early warning signal identify of water quality, and decision management. The study is applied to determining and analyzing the hazard degree of water quality safety in Songhua River Basin. Results show that the degree of water quality is in grade four, which is at serious alert. The practice and the result of the fuzzy evaluation method prove that it is feasible and scientific that the study combining RBF model with early warning system of water quality safety, and good effect is achieved.