Application of Kernel Function of Stock Price Forecasting Based on SVM
The paper conducted a regression forecast of Bank of China stock index.By selecting the optimal radial basis function, and then, for the optimal kernel function, we selected the parameter optimization using grid homing, genetic algorithm and PSO algorithm to build the most effective SVM model, and finally we predicted the opening number of the Bank of China in the next 15 days.The simulation shows that using SVM model to prediction Bank of China shares in the next 15 days the trend is very feasible.
support vector machineregression predictionopening quotation
国家科技期刊平台
NSTL
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