Forecasting of Gas Emission Based on Ant Colony Optimization RBF Network

摘要：

Because the gas has the property of nonlinearity and uncertainty,it is very difficult for us to forecast precisely the gas emission quantity. The approach is proposed that ant colony clustering algorithm is combined with RBF neural network to forecast the gas emission,using ant colony clustering algorithm to get the center of hidden layer neurons. To find the best clustering result,local search is applied in ant colony algorithm. This model has good performance of strong local generalization abilities and satisfying accuracy. At last,it is proved with lots of experiments that the application is fairly effective.

关键词： gas emission ant colony clustering RBF neural network local search

作者: Chunfeng Song Yuanbin Hou Ning Li

作者单位: The Institute of Electric and Control Engineering,Xian University of Science and Technology,Xian,China

会议类型: 国际会议

会议名称: 2011 International Conference on Opto-Electronics Engineering and Information Science(2011光电电子工程与信息科学国际会议 ICOEIS 2011)

会议地点: 西安

会议语种:英文

页码: 303-307

在线出版日期: 2011-12-23（万方平台首次上网日期，不代表论文的发表时间）