Rabab Hamed M. Aly1,*, Aziza I. Hussein2, Kamel H. Rahouma3
CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3985-3997, 2022, DOI:10.32604/cmc.2022.025862
- 29 March 2022
Abstract This paper aims to design an optimizer followed by a Kawahara filter for optimal classification and prediction of employees’ performance. The algorithm starts by processing data by a modified K-means technique as a hierarchical clustering method to quickly obtain the best features of employees to reach their best performance. The work of this paper consists of two parts. The first part is based on collecting data of employees to calculate and illustrate the performance of each employee. The second part is based on the classification and prediction techniques of the employee performance. This model is More >
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