Title :
Application of DM in E-Government Based on Combined Grey Neural Network
Author_Institution :
Sch. of Civil Eng., Hebei Univ. of Eng. Handan, Handan, China
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;
Conference_Titel :
Innovation Management, 2009. ICIM '09. International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-0-7695-3911-9
DOI :
10.1109/ICIM.2009.19
