摘要
介绍了基于BP(Back Propagation)神经网络建立市场销售预测模型的设计方法。针对BP算法的不足之处提出了改进措施:给网络参数赋初值;对原输入信息表达空间进行归一化;修正权重系数;将所有数据作为样本输入网络进行训练等。实验预测结果表明:BP算法适用于规则不可知的预测内容,它比常规方法具有更高的逼近精度和更好的预测能力。
A design way of setting up market forecasting model is introduced basing on Back-Propagation neural network. The improving method is put forward aiming at defect of BP algorithm： assigning initial value to network parameter; normalizing the expression space of original input message; revising the weighing coefficient; inputting all the datas to network for training as sample. The test forecasting result shows： BP algorithm is suitable for forecasting on some irregular questions. It has higher approximation precision and better forecasting ability than regular way.
关键词
BP神经网络
销售
预测
BP neural network
market
forecasting
