Study on Gas Emission Rate Prediction Based on Chaos Analysis

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.