Model for Evaluation of Water Quality Base on Improved Wavelet Neural Network

Abstract:

The nonlinear and uncertain of water environmental pollution,make the traditional water quality evaluation methods have limitations.In order to improve the accuracy of water quality evaluation,The paper put forward the water quality evaluation model based on improved wavelet neural network (Wavelet Neural Network, the WNN).Optimize the initial weights of wavelet neural network based on Adaptive Genetic Algorithm (Adaptive Genetic Algorithm, AGA),and then training the network by used wavelet neural network algorithm,finally,testing the trained network.The simulation results show that the combination of Adaptive genetic algorithm and wavelet neural network improved the efficiency of network training,and this method can be used in water quality evaluation, and the evaluation result has high precision and accuracy.

• Periodical: Applied Mechanics and Materials (Volume 700)
• Pages: 538-541
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.700.538
• Online since: December 2014
• Authors: Zhi Wu Yu, Jin Xia Ren, Xin You
• Keywords: Adaptive, Evaluation Model, Genetic Algorithm (GA), Water Quality Evaluation, Wavelet Neural Network

References

[1] Gonghu Niu, Yanling Shang. Water Quality Evaluation Based on Fuzzy Neural Network. computer simulation. 2012; 29(4): 173-176.

[2] Zhang Q H, Benveniste A. Wavelet network. IEEE Trans on Neural Network. 1992; 3(6): 889-898.

[3] Yue Zhao, Tingting Ru. New theory and application of genetic algorithm. Light Industry Science and Technology. 2014: 77-78.

[4] Yue Zhao, Xin Xu, Yan Zhao, etc. Research on Adaptive Memory Genetic Algorithm. Computer Technology And Development. 2014; 24(2): 63-66.

[5] Feng Shi , Xiaochuan Wang. 30 cases of MATLAB neural network. Beijing: press of university of aeronautics and astronautics. (2011).