Research on the Intelligent Modeling System Based on the Combination of the Genetic Wavelet Neural Networks and the Component Technology
Lan Qiu-ping · Computer Engineering and Science · 2007
A combined intelligent information processor is developed based on recombining and improving artificial neural networks(ANN),wavelet transformation(WT),and genetic algorithm(GA). Firstly, mass historical data and field data gathered by multi-sensors on spot are preprocessed using wavelet analysis,which takes the preprocessed data as the input sample of the neural network model,and the synchronously genetic algorithm which has the ability of global optimization is adopted to dynamically modify the network structure and parameters and eliminate the rate tardiness of neural network training and relapse into local extremum. This processor can be used for accomplishing complex nonlinear modeling and data mining.Finally, an intelligent modeling system with good expansibility is established by integrating the combined intelligent information processor with GIS using the component technology, and the integrated scheme is described clearly in this paper. In order to verify the feasibility and validity of the modeling methods,a simulation example is given for the runoff forecasting of an irrigation catchment.