Model of Gas Concentration Forecast Based on Chaos Theory

Abstract 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 one-rank 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.