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Proposing an Optimization Algorithm for Employee Competencies Evaluation using Artificial Intelligence Methods: Bayesian Network and Decision Tree
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 71 - Number 5 |
| Year of Publication: 2013 |
| Authors: Kamal Moh’d Alhendawi, Ahmad Suhaimi Baharudin |
10.5120/12354-8666
|
Kamal Moh’d Alhendawi, Ahmad Suhaimi Baharudin . Proposing an Optimization Algorithm for Employee Competencies Evaluation using Artificial Intelligence Methods: Bayesian Network and Decision Tree. International Journal of Computer Applications. 71, 5 ( June 2013), 18-22. DOI=10.5120/12354-8666
Abstract
Recently, the multidisciplinary research has been highly considered by the computer sciences researchers as it contributes to the innovation in terms of concepts and practices. This paper keeps special focus on the employment of belief network including influence and Bayesian nets models in modeling the uncertainties and decision making process. It attempts to model and optimizes one of the most important functions of the human resources called Competency Based Evaluation (CBE). Consequently, the present study is concerned with modeling the uncertainties of the CBE through AI modeling approaches as well as developing a new optimization algorithm towards decreasing the evaluation features of the employee performance. The developed algorithm aims at finding the decision regarding the performance based on Pearl's algorithms, where the conditional probabilistic is employed in order to decide regarding the employee performance based on his competencies. MATLAB is actually used for the implementation and empirical analysis purposes. The encouraging results of the study provide empirical evidence on the efficiency of the proposed algorithm as this algorithm minimizes the evaluation features. Thus, it would contribute to the enhancement of the competency based evaluation.
References
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