On new statistical modes of comprehensive earthquake forecast

In the research of projection pursuit for seismic comprehensive forecast, the projection pursuit regression (PPR) algorithm is one of most applicable methods. But the algorithm is very complicated. By partial smooth regressions for many times, it needs much computation and complicated extrapolation, so it is easily trapped in partial solution. In this paper, some modifications are given to optimize project direction by using particle swarm optimization(PSO), to simplify the optimal process with fitting ridge function by using Hermitian polynomial. The overall optimal ridge function can be obtained without grouping the parameter optimization. The modeling capability and calculating accuracy of the modified PPR are tested by means of numerical simulation based on the PSO and Hermitian polynomial, and then applied to the seismic comprehensive forecasting from the poly-dimensional seismic samples. The calculation and analysis show that the modified PPR in this paper is characterized by simplicity, celerity and effectiveness. And this model is approved to have satisfactory effects in the real seismic comprehensive forecasting.