基于多维数据挖掘的智慧城市经济管理效率综合评价模型

Ziyu Xu, Jingpeng Wu
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引用次数: 0

摘要

为了提高智慧城市经济管理效率的综合评价质量,将多维数据挖掘技术应用于智慧城市经济管理效率的综合评价建模。为了避免大样本问题造成的类间最大距离问题,采用MMC算法从多个维度挖掘多维数据,包括智慧城市经济管理的现状、合理性和管理模式。基于智慧城市经济的多维数据,有必要构建一个评价指标体系。计算各评价指标的权重,并对指标进行量化,以消除维度的影响。结合熵和变异系数,计算出智慧城市经济管理效率综合评价指标的计算模型。实验结果表明,与传统的评价方法相比,文本方法能够保证评价效率,提高评价精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comprehensive evaluation model of smart city economic management efficiency based on multidimensional data mining
In order to improve the comprehensive evaluation quality of the economic management efficiency of smart city, multidimensional data mining technology is applied to the comprehensive evaluation modeling of the economic management efficiency of smart city. In order to avoid the maximum distance between classes caused by the large sample problem, MMC algorithm is used to mine multi-dimensional data from multiple dimensions, including the status, rationality and management mode of smart city economic management. Based on the multi-dimensional data of smart city economy, it is necessary to build an evaluation index system. The weight of each evaluation index is calculated, and in order to eliminate the influence of dimension, the index is quantized. Combined with entropy and coefficient of variation, the calculation model of comprehensive evaluation index of smart city economic management efficiency is calculated. The experimental results show that, compared with the traditional evaluation methods, the text method can ensure the evaluation efficiency and improve the evaluation accuracy.
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