基于模糊网格划分的Mamdani方法在加薪资格决策支持系统中的应用

Murni Marbun, Sandhuri -, Aishwarya -
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引用次数: 0

摘要

采用模糊网格划分的方法,得到合适的最优输出。通过网格划分,改进了Tsukamoto法和Mamdani法等几种模糊推理方法的输出。本研究旨在应用基于模糊网格划分的mamdani方法来确定员工加薪的可行性。该方法的各个阶段从确定分区数、形成模糊集开始,进行隐式规则的生成过程,通过选择可行决策和不可行决策的最大值进行规则组合,最后进行去模糊化过程,得到crips值的计算结果。选择加薪资格的属性或特征是员工状态、类别状态、服务年限和获得的福利。研究的结果让每个员工决定是否应该加薪。从样本X7上测试的一个样本数据来看,去模糊化的结果(Z)为5。根据可行决策和不合适决策表,Z = 5的值属于可行决策
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of The Fuzzy Grid Partition-Based Mamdani Method to Decision Support System for Determining Salary Increase Eligibility
Fuzzy grid partition has been used to produce appropriate and optimal output. The output of several fuzzy inference methods such as the Tsukamoto method and the Mamdani method have been improved by applying grid partitions. This study aims to apply the fuzzy grid partition-based mamdani method to determine the feasibility of increasing employee salaries. The stages of the method are carried out starting with determining the number of partitions, forming fuzzy sets, carrying out the process of implicit rules, carrying out rule composition by selecting the maximum value of feasible and infeasible decisions, and finally carrying out the defuzzification process to obtain the calculation of the crips value. Attributes or features for selecting the eligibility for a salary increase are employee status, class status, years of service and benefits received. The results of the research get a decision for each employee whether it is appropriate to receive a salary increase or not. From one sample data tested on sample X7, the result of defuzzification (Z) is 5. Based on the table of feasible and inappropriate decisions, the value of Z = 5 is in a feasible decision
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