DocumentCode
3112341
Title
Application of DM in E-Government Based on Combined Grey Neural Network
Author
Qu Zhiming
Author_Institution
Sch. of Civil Eng., Hebei Univ. of Eng. Handan, Handan, China
fYear
2009
fDate
8-9 Dec. 2009
Firstpage
51
Lastpage
54
Abstract
Using grey system, satisfaction mining (DM) technology and radial basis function (RBF) neural network method, the combined model of grey system and RBF neural network is setup, which aims at solving the problems of E-government. The results show that, in short-term prediction, grey system is an effective way and RBF has perfect ability to study. The combined grey neural network (CGNN) has the dual properties of trend and fluctuation under the condition of combining with the time-dependent sequence satisfaction. It is concluded that great improvement comparing with any methods of trend prediction and simple factor in CGNN is stated and described in E-government.
Keywords
government data processing; grey systems; radial basis function networks; E-government; combined grey neural network; grey system; radial basis function neural network method; satisfaction mining technology; time-dependent sequence satisfaction; Civil engineering; Data mining; Decision making; Delta modulation; Electronic government; Fluctuations; Innovation management; Logic; Neural networks; Predictive models; CGNN; DM; E-government; RBF neural network; grey system;
fLanguage
English
Publisher
ieee
Conference_Titel
Innovation Management, 2009. ICIM '09. International Conference on
Conference_Location
Wuhan
Print_ISBN
978-0-7695-3911-9
Type
conf
DOI
10.1109/ICIM.2009.19
Filename
5381291
Link To Document