A forecasting model of RBF neural network based on genetic algorithms optimization

A new method of gas emission forecasting based on the optimized RBF network is presented. In this method, genetic algorithm (GA) is applied to optimize the position of data centers, widths, and weights of the RBF network, so forming a GA-RBF model. The principle and algorithms of neural network are...

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Bibliographic Details
Main Authors: Yumin Pan, Weining Xue, Quanzhu Zhang, Liyong Zhao
Format: Conference Proceeding
Language:English
Subjects:
Coal
Forecasting
gas emission
genetic algorithm (GA)
Genetic algorithms
Optimization
Predictive models
Radial basis function networks
RBF neural networks
Training
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Summary:A new method of gas emission forecasting based on the optimized RBF network is presented. In this method, genetic algorithm (GA) is applied to optimize the position of data centers, widths, and weights of the RBF network, so forming a GA-RBF model. The principle and algorithms of neural network are introduced. The simulation results show that the improved RBF neural networks has high precision, with reliable accuracy, good convergence rate and fast network training speed. Compared with the traditional RBF and BP networks, the method is more efficient and feasible.
ISSN:2157-9555
DOI:10.1109/ICNC.2011.6022042