候选评定与选择的模糊化技术

IF 0.6 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS International Journal of Decision Support System Technology Pub Date : 2022-01-01 DOI:10.4018/ijdsst.303944
Iwasokun Gabriel Babatunde, Ayowole Oluwatayo Idowu, B. Kuboye
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引用次数: 0

摘要

传统的选人招聘方式存在主观性、不精确性和模糊性等问题。为了在跟上技术进步和变化的同时实现客观、精确的选拔和招聘,本文讨论了一种基于模糊化的候选人评价和选拔技术。该技术包括模糊逻辑组件,它是布尔逻辑的扩展,用于建立精确的选择过程和多变量问题的精确解。知识库组件构成多层次的信息数据库,规则库组成一组if-then语句,用于决策。它的推理引擎对来自规则库和模糊逻辑接口的输入应用预定义的过程,以获得最终的建议。所提出的方法执行基于一些输入集的预定义程序,这些输入集存储来自几个预先指定的分数的多级信息。应用结果表明,该技术具有一定的实用功能。
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Fuzzification Technique for Candidate Rating and Selection
The traditional ways of candidate selection and recruitment are prone to subjectivity, imprecision and vagueness. With a view to achieving objective and precise selection and recruitment while keeping up with technological improvement and changes, this paper discusses a fuzzification-based technique for candidate rating and selection. The technique comprises a fuzzy logic component that is an extension of Boolean logic and used for establishing accurate selection process and precise solutions to multi-variable problems. There is a knowledge base component which forms the database of multi-level information and rule base which composes a set of if-then statements for decision making. Its inference engine applies a pre-defined procedure on input from the rule base and fuzzy logic interfaces for final recommendations. The proposed methodology performs pre-defined procedures that are based on some input sets which stores multi-level information derived from several pre-specified scores. Results from the implementation of the proposed technique established its practical function.
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来源期刊
International Journal of Decision Support System Technology
International Journal of Decision Support System Technology COMPUTER SCIENCE, INFORMATION SYSTEMS-
CiteScore
2.20
自引率
18.20%
发文量
40
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