Evaluation of knowledge complementary degree for creative industry cluster based on BP neural networks

Abstract

Creative industries are intelligent, highly knowledgeable. Cluster model increasingly becomes the main economic organization form of the world creative industry. Getting complementary knowledge and realizing the knowledge complementary within creative industry cluster is the main motivation of each cooperator. What's more, the complementary degree of knowledge also determines the development altitude of creative industry cluster. So, the BP neural network model was applied to evaluate the degree of knowledge complementary within the creative industry cluster. This paper constructs the creative industry cluster evaluation index system of knowledge complementary degree. Simultaneously, the paper has proposed the method to evaluate the creative industry cluster knowledge complementary degree based on BP Neural Networks. The study indicates that BP neural network is a model without linear mapping. It can give a satisfactory effort while the indices with a high level of correlation, nonlinear changing and data lacking. So, it's a relatively optimum method used for forecasting, with wide applying area and high value of popularizing.