Because stock forecasting is a uncertain, nonlinear and nonstationary time series problem, it is difficult to achieve a satisfying prediction effect by traditional methods.
由于股票预测是不确定、非线性、非平稳的时间序列问题，传统的方法往往难以取得满意的预测效果。
The proceeds of stock investment always equal the risk. So establishing a stock forecasting model, which has higher operation rate and precision, has theoretical significance and applicable value.
由于股票投资的收益与风险往往是成正比的，如何建立一个运算速度和精确度都比较高的股市预测模型，对于金融投资者具有理论意义和实际应用价值。
This paper mainly discusses the application of B-P network in stock forecasting and analysis. contrasts the network function in different conditions.
该文主要研究人工神经网络中的B-P网在股票分析和预测中的应用，对比各种情况的网络性能。
This paper mainly discusses the application of B-P network in stock forecasting and analysis. contrasts the network function in different conditions.
该文主要研究人工神经网络中的B-P网在股票分析和预测中的应用，对比各种情况的网络性能。
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