Study on Gas Emission Rate Prediction based on Chaos Analysis

摘要：

In order to realize the dynamic prediction on gas emission rate and avoid constructing a model, a study is carried out through chaos theory on the gas emission rate in this paper.On the basis of testing and verifying the gas emission rate to have chaotic characteristics, the Cao method is adopted to recognize embedding dimension and the mutual information method is used to recognize time delay, to reconstruct the phase spaces equivalent to the original system.In phase space, the prediction model base on both local region method and global method to realize the short-term prediction on the gas emission rate. The global method based on the BP neural network shows a good performance.Thus, the application of the chaos theory to the prediction on the gas emission rate is feasible.

关键词： Prediction on Gas Emission Rate Chaotic Time Series Reconstruction of Phase Space BP Neural Network

作者: Liu Yang Shi Qingjun Li Jing Ma Huibin Liu Desheng

作者单位: School of Information and Electronics Technology,Jiamusi University,Jiamusi,Heilongjiang,154007 China

会议类型: 国际会议

会议名称: International Conference on Advances in Engineering 2011(2011年工程研究进展国际学术会议 ICAE2011)

会议地点: 南京

会议语种:英文

页码: 106-110

在线出版日期: 2011-12-17（万方平台首次上网日期，不代表论文的发表时间）