BP 神经网络数据预测模型的建立及应用磁

摘要

Aiming at the problem of input node ,initial connection weights and excitation function .the establishment and improvement of the prediction model of BP neural network are discussed .The generation reasons and influencing factors of house price based on the data of house price in Guiyang (1998~2013) are analyzed ,then the prediction model of house price in Guiyang is built ,using the improved BP neural network .Finally the model's effectiveness and accuracy are validated by experiments .The results show that the relative error of the model prediction results is less than 0 .6% .%针对BP神经网络输入节点、初始权值的选取和激励函数问题，讨论BP神经网络预测模型的建立与改进。然后构建改进后的BP神经网络预测模型，并以贵阳市1998年～2013年的房价及其影响因素的数据为基础，通过实验验证该改进模型的有效性和精确性；结果表明采用论文模型预测结果相对误差不超过0．6％。