Model of Gas Concentration Forecast Based on Chaos Theory

摘要：

By means of chaos system predictability in the short term, model of coal gas concentration forecast was constructed. Based on Takens theorem, the phase space was reconstructed from the time series of gas concentration, and the optimal time delay and embedding dimention was proposed by using C-C arithmetic.In high dimention phase space, the model of gas concentration forecast using add-weighted onerank local-region method was constructed, the real gas concentration data was analyzed, and the future data of the coal mine were forecasted. The results show that maximum Lyapunov exponent is 0.049, the time series is chaotic, and in the phase space, time delay is 7, embedding dimention is 2, the model parameter a is 0.0228, b is 1.0859, the relative error is -0.2～0.2, and RMSE(root mean square error) is 0.0423. The predictive results tally with the real ones, which can be used to forecast the coal gas concentration in the short future.

关键词： chaos gas concentration reconstructed phase space weighted one-rank local-region method

作者: Zhai Shengrui Nie Baisheng Liu Shuiwen Wang Hui Zhao Caihong Li Qian Li Hailong

作者单位: School of Resource & Safety engineering, China University of Mining & Technology, Beijing, 100083,Ch Changzhou Automation Research Institute of CCTEC, Changzhou 213015, China

会议类型: 国际会议

会议名称: The First International Symposium on Mine Safety Science and Engineering (首届矿山安全科学与工程学术会议)

会议地点: 北京

会议语种:英文

页码: 197-203

在线出版日期: 2011-10-27（万方平台首次上网日期，不代表论文的发表时间）