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Construction of the Public Management Performance Assessment Algorithm Using Fuzzy Clustering

机译:基于模糊聚类的公共管理绩效评估算法的构建

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摘要

This paper analyzes the limitations of the current public management performance evaluation system,puts forward a public management performance evaluation model based on fuzzy clustering,and expounds on the theoretical framework and principle of this method. In addition,this paper introduces the concept and method of public management performance evaluation into the evaluation content system of government under the rule of law and realizes the combination of government under the rule of law theory and public management performance evaluation methodology. At the same time,through the analysis of the organizational system,technical system,institutional mechanism,result orientation,public satisfaction,and related index content,a public management performance evaluation index system is designed. Through macro and micro,qualitative and quantitative analysis and evaluation,the performance evaluation index system is improved,which provides an objective basis for forecasting and decision-making,control,and adjustment. The research shows that the highest accuracy of this clustering method can reach about 96,and its accuracy is about 10 higher than that of the ID3 algorithm. It is expected that this research can make some contributions to the research of the public management performance evaluation index system. At the same time,it highlights the importance of research on performance evaluation of government ruled by law.
机译:本文分析了当前公共管理绩效评价体系的局限性,提出了一种基于模糊聚类的公共管理绩效评价模型,阐述了该方法的理论框架和原理。此外,本文将公共管理绩效评价的概念和方法引入法治政府评价内容体系,实现法治下政府理论与公共管理绩效评价方法论的结合。同时,通过对组织体系、技术体系、体制机制、结果导向、公众满意度以及相关指标内容的分析,设计了公共管理绩效评价指标体系。通过宏观和微观、定性和定量的分析评价,完善了绩效评价指标体系,为预测决策、控制和调整提供了客观依据。研究表明,该聚类方法的最高准确率可达96%左右,其准确率比ID3算法高出约10%。本研究有望为公共管理绩效评价指标体系的研究做出一定贡献。同时,强调了法治政府绩效评价研究的重要性。

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