Abstract
It is quite challenging for the human resource management professionals to deal with the employees’ salary expectations compared to their work during the salary increment period. Employees’ salary is raised based on some major factors which include their mastery, responsibility, workload factors and many more. For the salary increment, the employee’s performance is estimated based on crisp values. This estimation leads to uncertainty and vagueness. In order to handle this situation of uncertainty, we have proposed the use of fuzzy logic in salary increment model. Our data set consists of the salary increment factors of the employees along with the increased salary percentage of 100 employees. The implementation of Adaptive Neuro Fuzzy inference system (ANFIS) on salary increment model is described in this paper. We have approached the Sugeno fuzzy inference model to generate the fuzzy rules and membership functions of input (salary increment factors) and output (salary increment percentages) data.
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Mobasshera, A., Naher, K., Rezoan Tamal, T.M., Rahman, R.M. (2019). Salary Increment Model Based on Fuzzy Logic. In: Silhavy, R. (eds) Artificial Intelligence and Algorithms in Intelligent Systems. CSOC2018 2018. Advances in Intelligent Systems and Computing, vol 764. Springer, Cham. https://doi.org/10.1007/978-3-319-91189-2_34
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DOI: https://doi.org/10.1007/978-3-319-91189-2_34
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