基于RBF神经网络的总产值预测模型研究  

Research on Predicting Model of Gross Production Value Using RBF Neural Network

作　　者：张亚平[1] 张立伟[2] 

机构地区：[1]黑龙江科技学院数力系,黑龙江哈尔滨150001 [2]哈尔滨工程大学自动化学院,黑龙江哈尔滨150001

出　　处：《吉林师范大学学报（自然科学版）》2006年第4期27-28,共2页Journal of Jilin Normal University:Natural Science Edition

摘　　要：介绍了径向基函数(RBF)神经网络的工作原理和训练算法．根据生产总值与投资分配之间存在的映射关系,应用RBF神经网络建立了投资预测模型,并进行了仿真试验．与BP模型相比,该模型在预测精度和收敛速度方面具有显著的优点．结果表明,用RBF神经网络进行投资预测得到了十分满意的结果．The work theory and training algorithm of RBF Neural Network were presented in this paper. A predicting model of investment was established on the mapped relationship between gross production value and distribution of investment using RBF neural Network and a simulation was done. Compared with BP model, it had apparent advantages in predicting precision and convergence rate. The predicting result indicated that it was well -content to predict using RBF Neural Network.

关 键 词：RBF神经网络 投资预测 总产值 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]