Title :
A new water quality evaluation model based on simplified Hopfield neural network
Author :
Rong, Li ; Junfei, Qiao
Author_Institution :
School of Electric Information and Control Engineering, Beijing University of Technology, Beijing 100124, China
Abstract :
The evaluation of water quality plays a very important part in water resources protection. Compared with other methods, Hopfield neural network can evaluate the water quality effectively. Aiming at the problem of complicated structure of Hopfield neural network, a simplified model is proposed. In the simplified model, connection weights are designed by singular value decomposition to improve running speed. And the simple structure is got by deleting unimportant weights. Finally, the effectiveness and feasibility of simplified model is proved for water quality evaluation.
Keywords :
Data models; Hopfield neural networks; Indexes; Neurons; Standards; Testing; Water pollution; Hopfield neural network; evaluation criteria; simplified model; water quality evaluation;
Conference_Titel :
Control Conference (CCC), 2015 34th Chinese
Conference_Location :
Hangzhou, China
DOI :
10.1109/ChiCC.2015.7260184
