Toward work groups classification based on probabilistic neural network approach

Abstract

This paper presents the application of some Computational Intelligence methods for obtaining a classifier analysing employees to form work groups. The proposed bio-inspired solution analyses employees using data gathered from their professional attitudes and skills, then suggests how to form groups of human resources within a company that can effectively work together. The same proposed tool provides employers with a fair and effective means for employee evaluation. In our approach, employee profiles are processed by a dedicated Radial Basis Probabilistic Neural Network based classifier, which finds non-explicit custom-created groups. The accuracy of the classifier is very high, revealing the potential efficacy of the proposed bio-inspired classification system.