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Modelling Work Motivation with a Fusion ARTMAP Neural Network

p. 85-100

Abstract

This paper seeks to introduce the ARTMAP family of artificial neural networks as a mathematical theory for modelling work motivation. A new type of construction of psychometric scales based on Fuzzy ART modules is proposed. Psychological relations are modelled with the ARTMAP processing mechanism. Two variations - Fuzzy and Fusion are evaluated with respect to a psychological database. The results achieved are preliminary, but give clear indication of the method's potential. Due to the high precision, capacity for individualisation of the information, and better use of the raw data by Fusion ARTMAP, it can be of much help in organizational research. More specifically, human resources management may benefit from the opportunity to use computer simulations of on-going human interaction processes.

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References

Bibliographical reference

George D. Mengov, Irina L. Zinovieva and George R. Sotirov, « Modelling Work Motivation with a Fusion ARTMAP Neural Network », CASYS, 3 | 1999, 85-100.

Electronic reference

George D. Mengov, Irina L. Zinovieva and George R. Sotirov, « Modelling Work Motivation with a Fusion ARTMAP Neural Network », CASYS [Online], 3 | 1999, Online since 07 October 2024, connection on 27 December 2024. URL : http://popups.uliege.be/3041-539x/index.php?id=818

Authors

George D. Mengov

Technical University of Sofia, Studentski Grad, 1756 Sofia, And Unisys Bulgaria, Tzarigradsko Sh. 7 km, 1784 Sofia

Irina L. Zinovieva

Department of Psychology, Sofia University "St. Kliment Ohridski, Tzar Osvoboditel 15, 1000 Sofia

George R. Sotirov

Department of Industrial Automation, Technical University of Sofia, Studentski Grad, 1756 Sofia

Copyright

CC BY-SA 4.0 Deed