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Evaluative Research into E-government Sites Based on BP Neural Network

机译:基于BP神经网络的电子政务网站评价研究。

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After analyzing various evaluation index systems of E-government sites, issues were studied such as too many indices, hardly-quantified and easily- correlated indices.Principal Component Analysis Method was adopted firstly to screen out the main one from a great many evaluation factors. The dimension was declined effectively on condition that evaluation information was reserved. The E-governmental website's quantitative evaluation is gained by the self-study function of the BP neural network. With the application and verification in E-government sites of Hangzhou 2005, it has proved that the model has a good universal property, robustness and reliability. It supplies a new valid way of evaluation in E-government sites.
机译:在分析了电子政务站点的各种评价指标体系之后,研究了指标过多,难以量化,容易相关的问题。首先采用主成分分析法从众多评价因素中筛选出主要指标。在保留评估信息的前提下,有效降低了维度。电子政府网站的定量评估是通过BP神经网络的自学习功能获得的。通过2005年杭州市电子政务站点的应用和验证,证明该模型具有良好的通用性,鲁棒性和可靠性。它为电子政务站点提供了一种新的有效评估方法。

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