基于BP神经网络的高新区公共服务质量评价模型研究

Research on Public Service Quality Evaluation Model of High-tech Industrial Development Zone Based on BP Neural Network

基于太原市高新区的调查数据,应用因子分析和BP神经网络相结合的评价方法构建了高新区公共服务质量评价模型并对模型加以训练和仿真验证.结果表明:1)通过因子分析法实现了降维,有效提高BP网络的学习效率和收敛速度;2)较好的提高了评价结果的准确性和模型的外推能力.研究提升了高新区公共服务质量评价的精准性和科学性,为相关的研究提供了一种新的视角和评价方法.

Based on the survey data of Taiyuan High-tech Zone,the application of factor analysis and BP neural network combined evaluation method to construct the public service quality evaluation model of high-tech zone and train and simulate the model.The results show that:(1)the dimension reduction method is used to achieve dimensionality reduction,and the learning efficiency and convergence speed of the BP network are effectively improved.(2)The accuracy of the evaluation results and the extrapolation ability of the model are improved.The research in this paper improves the accuracy and scientificity of public service quality evaluation in high-tech zones,and provides a new perspective and evaluation method for related research.