A Fuzzy Comprehensive Evaluation System for Performance Appraisal Based on Clustering Algorithm

Kai Zhang ()
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Kai Zhang: Gusu Laboratory, General Management Department

A chapter in Proceedings of the 2023 3rd International Conference on Financial Management and Economic Transition (FMET 2023), 2024, pp 178-185 from Springer

Abstract: Abstract In response to the traditional performance evaluation methods that require a large amount of manpower and material resources to be uniformly allocated, and the storage methods of input data are not unified, resulting in low evaluation efficiency and accuracy, a performance evaluation fuzzy comprehensive evaluation system design method based on K-means clustering algorithm is proposed. The system consists of a data preparation module, a performance evaluation fuzzy evaluation module, a report processing module The system maintenance module constitutes the overall structure of the performance evaluation fuzzy comprehensive evaluation system. Using the Analytic Hierarchy Process to calculate the corresponding weights of performance evaluation indicators, a fuzzy evaluation model for performance evaluation is constructed. The K-means clustering algorithm is used to solve the fuzzy comprehensive evaluation model for performance evaluation, achieving the evaluation of performance evaluation and completing the design of the fuzzy comprehensive evaluation system for performance evaluation. The experimental results show that the evaluation efficiency and accuracy of this method are high.

Keywords: K-means clustering algorithm; Performance evaluation; Fuzzy evaluation; system design (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:spr:advbcp:978-94-6463-272-9_19

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DOI: 10.2991/978-94-6463-272-9_19

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