Evaluation of Regional Economic Innovation Ability Based on Neural Network

Abstract

In order to further improve regional economic innovation capability and governance level and solve the problems of lack of attention to evaluation indicators in traditional evaluation methods of regional economic innovation capability and easy to be affected by subjective factors, an evaluation model based on neural network algorithm is proposed. Through re-analysis of regional economic innovation capability evaluation indexes, the model defines the most reasonable combination of characteristics by combining information gain characteristic selection strategy and finally builds a scientific evaluation index system. By testing the prediction accuracy of the experimental discovery model and evaluation index, the neural network model improves by 41% compared with the traditional subjective evaluation method, and the accuracy increases by 20% compared with the GA-BP neural network model. The experiment proves the stability and good convergence effect of the evaluation model.