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Received:December 02, 2011 Revised:March 06, 2012
Received:December 02, 2011 Revised:March 06, 2012
中文摘要: 神经网络是数据挖掘的常用的方法之一,主成分分析方法是统计学多元分析中的一种分析多个变量间内在关系的方法。将主成分分析预处理方法与神经网络结合起来使用,可以分析原始变量间关系,将原始数据降维,减少数据规模。对神经网络算法和主成分分析相关理论进行了研究,在此基础上,结合大量的气象数据和北京的传染病数据,提出了一种改进的基于主成分分析预处理结合神经网络算法的数据挖掘方法。通过对比实验测试,本文提出的组合算法在收敛速度及预测准确性方面的性能有了很大程度提高。结合国家重大专项疾病预测项目,将该方法应用于其中的流行性
Abstract:The neural network is a kind of the commonly used method of data mining, principal component analysis method is a kind of method that analyzes internal relationship between the many variables of the multivariate analysis of statistical. Combined the principal component analysis pretreatment method with neural network, you can analyze the relationship between the original variables, reduce dimensions of the original data and reduce the scale of data. This paper does research on the neural network algorithm and the principal component analysis correlative theory. Based on this, combined with a large number of meteorological data and disease data of Beijing, we proposed an improved method of the data mining which based on principal component analysis and neural network algorithm preprocessing. Through the contrast experiment test, the combinations of the algorithm have a large degree increase in the convergence rate and forecast accuracy property.
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基金项目:国家科技重大专项(2012ZX10004-301-609);国家自然科学基金(60970128)
引用文本:
王行甫,覃启贤,程用远,侯成龙.一种改进的径向基神经网络预测算法.计算机系统应用,2012,21(8):214-217
WANG Xing-Fu,QIN Qi-Xian,CHENG Yong-Yuan,HOU Cheng-Long.Improved RBF Neural Network Prediction Algorithm.COMPUTER SYSTEMS APPLICATIONS,2012,21(8):214-217
王行甫,覃启贤,程用远,侯成龙.一种改进的径向基神经网络预测算法.计算机系统应用,2012,21(8):214-217
WANG Xing-Fu,QIN Qi-Xian,CHENG Yong-Yuan,HOU Cheng-Long.Improved RBF Neural Network Prediction Algorithm.COMPUTER SYSTEMS APPLICATIONS,2012,21(8):214-217