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

机译:基于BP神经网络的电子政务评价模型的研究与应用。

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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.
机译:在电子政务评估领域,借鉴平衡计分卡,建立了综合考虑资本投入,网站建设和应用效果等多种因素的指标体系。层次分析法和模糊综合评价模型(AHP-FCE)在应用范围上存在局限性,因为当评价对象数量较大时,难以快速建立一致性成对比较矩阵。因此,本文介绍了一种基于BP神经网络的电子政务评价模型。在随机生成的实例上进行的计算实验表明,该模型可用于求解大量评估对象,并已证明优于其他类似模型。

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