Title :
GA -RBF model and its application in evaluation of water quality
Author :
Zhu, Changjun ; Li, Sha ; Wu, Liping
Author_Institution :
Coll. of Urban Constr., Hebei Univ. of Eng., Handan, China
Abstract :
By combining GA (Genetic Algorithm), which has the advantage of global optimization, and RBF, which has the advantage of local optimization, the calculation accuracy and convergence rate of the traditional RBF neural network are improved. So a combinational evaluation model is presented based on GA and RBF neural network. And it is applied to comprehensive analysis and evaluation of water quality, not only retains the original merits of the neural network, but also overcomes these shortcomings, and establishes water quality evaluation model. The experimental results show that the hybrid algorithm model has evaluation of high precision, and can be applied to water quality evaluation. The simulation result shows this method has high convergent speed and easily oriented global optimization and is therefore of great practical value.
Keywords :
genetic algorithms; radial basis function networks; water resources; RBF neural network; combinational evaluation model; genetic algorithm; radial basis function network; water quality evaluation; Artificial neural networks; Biological neural networks; Convergence; Genetic algorithms; Genetic mutations; Intelligent networks; Intelligent transportation systems; Neural networks; Optimization methods; Signal processing algorithms; RBF neural network; genetic algorithm; water quality;
Conference_Titel :
Power Electronics and Intelligent Transportation System (PEITS), 2009 2nd International Conference on
Conference_Location :
Shenzhen
Print_ISBN :
978-1-4244-4544-8
DOI :
10.1109/PEITS.2009.5406848