Fractal Analysis And Chaotic Prediction Model For Gas Density Time Series

Gas outburst, as a grave natural disaster, is a great threat to the safe production of coal mine. Inspired by the multi-geological factors, Gas density had close relations directly with gas disaster like outburst. In order to acquire the accurate and quick prediction on the risk of coalmine gas outburst, experiments had been carried out at Pansan Coalmine in Huainan, Anhui Province. Range Fractal model was proposed for the analysis of gas density series after the detailed study of basic fractal characteristics of gas density time series, which consists of gas monitor density data. Chaotic time series analysis was applied to research the chaotic properties of gas density time series. The traditional chaotic forecast algorithm for gas series was ameliorated, and for gas time series 2 reformative and improved chaotic prediction models were established with greater performance and efficiency. Experiment results verified that using range fractal model could offer a qualitative prediction to the dynamical dangerous trends of gas density time series. The quantitive prediction results of both chaotic models appeared reliable and feasible as expected. After research on the gas outburst case of Pansan coalmine, the abnormal aspects were discovered in application of analyzing the relations between gas outburst and gas density time series before outburst. And some general evolution rules appeared clearly to explanations for gas outburst. These valuable discoveries are to be testified with more gas outburst data. On the basis of Multivariate Statistics, the evaluation model was proposed for gas outburst risk. Based on above all, design of the gas density prediction software was achieved and performed smooth as expected.