Extracting rules from trained neural network using GA for managing E-business

Theabilitytointelligentlycollect,manageandanalyzeinformationaboutcustomersandsellersisakeysourceofcompetitive advantage for an e-business. This ability provides an opportunity to deliver real time marketing or services that strengthen customer relationships. This also enables an organization to gather business intelligence about a customer that can be used for future planning and programs. This paper presents a new algorithm for extracting accurate and comprehensible rules from databases via trained artificial neural network (ANN) using genetic algorithm (GA). The new algorithm does not depend on the ANN training algorithms also it does not modify the training results. The GA is used to find the optimal values of input attributes (chromosome), Xm, which maximize the output function k of output node k. The function k = f(xi, (WG1)i,j, (WG2)j,k) is nonlinear exponential function. Where (WG1)i,j, (WG2)j,k are the weights groups between input and hidden nodes, and hidden and output nodes,...

• Type: Journal
• Year: 2004
• Where: ASC
• Authors: Atta Ebrahim E. ElAlfi, R. Haque, M. Esmel ElAlami
• Keywords: ASC 2004, ASC 2006, Customer Relationships, Output Nodes, Real Time Marketing