The Research Of Chaotic Prediction And Pattern Recognition Based On Omen Information Of Rock Burst

In this paper, based on lots of measured information, the nonlinear science such as chaos theory, wavelet analysis theory, neural network, and pattern recognition is applied to the analysis and prediction of rock burst, and chaotic prediction models and pattern recognition method of rock burst are proposed in this dissertation. The main contents are as follows.(l)For having prediction and recognition more accurate, a united method which uses wavelet transform and strange value decomposition eliminate noise is proposed. The method takes advantage of capability which wavelet eliminate noise of one dimension time series and feature of non-damage to data which strange value decomposition eliminates noise.(2)based on lots of measured information, chaotic character of observation scries to rock burst can be offered(made) by back-analysis of correlation dimension and Lyapunov exponent extracted from these series to have character and rule of rock burst can be researched deeply in the processing of its evolution. The results show that rock burst observation series is a chaotic series and that chaotic prediction and pattern recognition is feasible.(3)based on the results of chaos analysis, the chaotic prediction mode of rock burst observation data series based to one-order approximation model, Lyapunov exponent, and neural network. The prediction effect is good by analysis of practical example.(4)based on the results of chaotic analysis and prediction, using theory of pattern recognition, math feature values of observation series to rock burst including time domain, frequency domain, wavelet domain, and chaos domain are calculated. By comparison and selection to these feature values using the similarity measure criterion based to Euclidean distance measurement, the feature values mapping essence of observation series and being able to recognize...