Title :
Gas content prediction based on GA-RBF neural network
Author :
Zhai, Bo ; Shan, Jianfeng
Author_Institution :
Sch. of Comput. & Commun. Eng., Liaoning Shihua Univ., Fushun, China
Abstract :
Genetic algorithms (GA) and radial basis function (RBF) neural network are combined in this paper. Prediction model of gas content in coal seam is set up based on GA-RBF neural network optimized by genetic algorithm in network structure and parameters. The actual forecasting results show that the algorithm has higher prediction accuracy and faster computing speed and is helpful to mine gas disaster prediction and prevention.
Keywords :
air pollution; disasters; forecasting theory; gas industry; genetic algorithms; radial basis function networks; coal seam; gas content prediction model; genetic algorithms; mine gas disaster prediction; mine gas disaster prevention; network parameters; network structure; radial basis function neural network; Accuracy; Feeds; Function approximation; Gaussian processes; Genetic algorithms; Network topology; Neural networks; Neurons; Optimization methods; Radial basis function networks; RBF; gas prediction; genetic algorithm;
Conference_Titel :
Control and Decision Conference (CCDC), 2010 Chinese
Conference_Location :
Xuzhou
Print_ISBN :
978-1-4244-5181-4
Electronic_ISBN :
978-1-4244-5182-1
DOI :
10.1109/CCDC.2010.5498643
