Research and application of E-government evaluation model based on BP neural network

In the field of E-government evaluation, learning from the Balanced Scorecard, an index system is established which takes into account of various factors, including capital investment, website construction and application effect. The analytical hierarchy process and fuzzy comprehensive evaluation (AHP-FCE) model has a limitation of application scope, because it´s difficult to quickly construct the consistency pairwise comparison matrix when the number of evaluation objects is large. So this paper introduces an E-government evaluation model based on BP neural network. Computational experiments performed on randomly generated instances show that the proposed model can be used to solve large number of evaluation objects and has proved to be superior with other similar models.