吉林大学学报（理学版）Issue(6)：1263-1268,6.DOI:10.13413/j.cnki.jdxblxb.2015.06.36
基于残差修正的灰色神经网络在数据挖掘中的应用
Application of Gray Neural Network Based on Residual Correction in Data Mining
摘要
Abstract
In the light of the features of small sample size and some information unknown time series data,gray neural network was constructed by combining the gray theory with neural networks,which makes the full use of the advantage of the two kinds of approaches to realize the data mining of the small sample time series data effectively.Meanwhile,in order to improve the prediction accuracy of the model,the residuals were used for the model effective correction.The experiment results show that the proposed residual correction gray neural network has a high prediction accuracy,and is very suitable for the small sample time series data mining.关键词
数据挖掘/灰色理论/神经网络/残差修正Key words
data mining/gray theory/neural networks/residual correction分类
信息技术与安全科学引用本文复制引用
孙金岭,庞娟..基于残差修正的灰色神经网络在数据挖掘中的应用[J].吉林大学学报（理学版）,2015,(6):1263-1268,6.基金项目
国家自然科学基金(批准号:41121001 （）
41273010)、中国科学院知识创新群体项目(批准号:KZZD-EW-04-05-01)、中国科学院寒区旱区环境与工程研究所冰冻圈科学国家重点实验室项目(批准号:SKLCS-ZZ-2012-01-02)和中国科学院外国专家局创新团队国际合作伙伴计划项目 （批准号:KZZD-EW-04-05-01）
