Probabilistic Neural Network Model Based on Wavelet and Partical Swarm Optimization
Foreign exchange market is a complex market, with a high degree of volatility characteristics. Exchange rate formation mechanism and the factors affecting exchange rate volatility are also very complex, which is a nonlinear system. It is difficult to accurately forecast. Probabilistic neural network is applied to the frontiers of forecast, and aimed at the characteristics of probabilistic neural network to pretreat the exchange of data and forecast the tendency. And by changing the vector dimensionality experiment we obtain the best entry to embed dimensionality, tested and improved the precise prediction and valuable.
exchange rate forecast probabilistic neural network wavelet partical swarm optimization
WangHua Liu Bingxiang Cheng Xiang
Jingdezhen Ceramic Institute Jingdezhen, China
国际会议
上海
英文
2233-2235
2011-10-15（万方平台首次上网日期，不代表论文的发表时间）