计算机工程与应用2012，Vol.48Issue(4)：176-178,3.DOI:10.3778/j.issn.1002-8331.2012.04.052
基于优化模糊神经网络的CPI趋向预测
Consumer price index' s trend forecasting based on optimized fuzzy neural network
摘要
Abstract
The consumer price index is an important basis of consumer price index policy, salary policy, and national economy development strategies. Many researchers have carried out a lot of researches for CPI, and a lot of achievements have been got, however, past predicting method applies the simple neutral network method, and the good predicting results are difficult to be obtained. The paper puts forward a fuzzy rule self adaptive training algorithm according to the existing problems, and the fuzzy rules of different numbers are produced according to the actual problems, and the network structure is confirmed according to fuzzy rule. For the confirmation of the network structure, the test needs not be carried again and again because it can not be formed randomly. Therefore it is responsible. Simulation results show that this method gets the good effect for predicting consumer price index.关键词
消费价格指数/优化模糊神经网络/趋向预测Key words
consumer price index/ optimized fuzzy neural network/ trend forecasting分类
信息技术与安全科学引用本文复制引用
黄胜忠,黄天开..基于优化模糊神经网络的CPI趋向预测[J].计算机工程与应用,2012,48(4):176-178,3.基金项目
新世纪广西高等教改科研工程项目(No.2010JGB135) （No.2010JGB135）
高校教师教学反思的形式与效果的实践研究(No.LB2009A051). （No.LB2009A051）
