A Novel Water Quality Assessment Method Based on Combination BP Neural Network Model and Fuzzy System

As the forefront of complex nonlinear science and artificial intelligence science, artificial neural network has began to be applied in the field of water quality control and planning step by step. According to the fuzzy feature of water quality information, this paper proposes a membership degree Back-Propagation network (MDBP) for water quality assessment with combining fuzzy mathematics and artificial neural network. The proposed MDBP model combines the merits of artificial neural network method and fuzzy evaluation method, which overcomes effectively the shortcoming of other assessment methods. With improving the accuracy and reliability of the assessment method, the method has a higher flexibility than other conventional approach and its programs have a better adaptability and more convenient application. The assessment method is closer to the reality with considering the continuity of the changes of water quality environment.