Title :
Application of DM in data safety of machine learning based on combined grey neural network
Author :
Wang Yude ; Qu Zhiming
Author_Institution :
Sch. of Civil Eng., Hebei Univ. of Eng., Handan, China
Abstract :
Using the theory of grey system, DM technology and radial basis function (RBF) neural network method, a new model, the combined model of grey system and RBF neural network is setup, which aims at solving the user´s received data safety of machine learning. The results show that, in short-term prediction of data safety of machine learning, GM is an effective way and RBF has perfect ability to study and map. The combined model of grey system and neural network, to a large extent, has the dual properties of trend and fluctuation under the condition of combining with the time-dependent sequence data. It is concluded that great improvement comparing with any method of trend prediction and simple factor in combined grey neural network (CGNN) comparing with the any model of grey system and RBF neural network in data safety of machine learning of machine learning.
Keywords :
data mining; grey systems; learning (artificial intelligence); radial basis function networks; security of data; combined grey neural network; data mining; data safety; machine learning; radial basis function neural network method; time-dependent sequence data; Civil engineering; Communication system control; Computer networks; Data engineering; Data mining; Delta modulation; Machine learning; Neural networks; Predictive models; Safety; CGNN; DM; data safety of machine learning; machine learning;
Conference_Titel :
Computing, Communication, Control, and Management, 2009. CCCM 2009. ISECS International Colloquium on
Conference_Location :
Sanya
Print_ISBN :
978-1-4244-4247-8
DOI :
10.1109/CCCM.2009.5267463