The Evaluation Model of Knowledge Management Based on Information Entropy and RBF Neural Network (IE-RBF)

Knowledge management is a complex systems engineering, so the evaluation of knowledge management is of non-linear characteristics. Neural network with the ability of adaptive learning is an excellent tool to deal with the issue of non-linear. This paper analyzed the essence of knowledge and knowledge management. We proposed an evaluation model of knowledge management based on the theory of information entropy and RBF neural network. After reduction of the indices system with information entropy to reduce, we would evaluate the knowledge management with RBF neural network. After empirical research with MATLAB7.0, it is had been proved that the method is validity and practicality. And then it did not only overcome the traditional methods’ shortcoming which is too subjective, but also avoided complex process of the traditional evaluation method.