一种基于神经网络的电子政务网站评价方法

Chun-hua Ju, Ying Liang, Dong-sheng Liu
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引用次数: 7

摘要

本文提出了一种利用神经网络技术对电子政务网站进行性能评价的新方法。该评价模型基于BP神经网络和主成分分析,提高了网络的性能。保证了评价结果的客观性和科学性。该方法采用主成分分析法对大量数据进行分析,提取出主要评价因子。在保留评价信息的条件下,有效地降低了维度。采用BP神经网络确定各指标的权重。在确定评价指标权重时,削弱了评价人的随意性和主观性。通过对宁波市2006年电子政务站点的应用和验证,表明基于BP神经网络的模型具有广泛的前景和应用价值
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A kind of E-government website evaluation method based on Neural Network
This paper presents a new method to evaluate the performance of the e-government Website with neural network technology. The evaluation model, based on BP neural network and principal component analysis, raises the performance of the network. And it guarantees the objectivity and scientific of the evaluation result. This method analyzed a lot of data with principal component analysis method and the main evaluation factors were picked up. Dimensions were declined effectively on condition that evaluation information was reserved. BP neural network was used to fix on the weights of indices. It weakens the random and appraiser's subjectivity when fixing the index weight in evaluation. With the application and verification in e-government sites of Ningbo 2006, the model based on BP neural network has an extensive foreground and application value
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