Abstract

The aim of this study is to device a system based on fuzzy Petri nets for measuring employee performance. Fuzzy Petri net models are very helpful for specifying the expert systems with imprecise description of rules. Much research has been done for measuring human resource based on features like performance indicators generated in their work place. Such features are inherently challenging full to quantify as they are highly subjective and imprecise in nature. Concurrent and reliable systems can be realized or specified using Petri nets. Hence in this study, due to these limitations we focus on establishing the method for constructing fuzzy Petri net for the domain of human performance.

Keywords:

Fuzzy rules , high-level fuzzy Petri nets , performance measure,

References

1. Ding, W., L. Pei, H. Li, N. Xi and Y. Wang, 2009. The effects of time delay of internet on characteristics of human behaviors. Proceeding of the IEEE International Conference on Networking, Sensing and Control. Okayama, Japan.
   CrossRef    
2. Dorsey, D.W. and M.D. Coovert, 2003. Mathematical modeling of decision making: A soft and fuzzy approach to capturing hard decisions. Hum. Factors, 45(1): 117-135.
   CrossRef    PMid:12916585     
3. Duric, Z., W.D. Gray, R. Heishman, F. Li and H. Wechsler, 2002. Integrating perceptual and cognitive modeling for adaptive and intelligent human-computer interaction. P. IEEE, 90(7): 1272-1289.
   CrossRef    
4. He, X., W.C. Chu, H. Yang and S.J.H. Yang, 1999. A new approach to verify rule-based systems using petri nets. Proceeding of 23th IEEE Annual International Computer Software and Applications Conference (COMPSAC’99), pp: 462-467.
   PMid:11501088    
5. Kouzehgar, M., M.A. Badamchizadeh and S. Khanmohammadi, 2011. Fuzzy Petri nets for human behavior verification and validation. Int. J. Adv. Comput. Sci. Appl., 2(12): 106-114.
   CrossRef    
6. Kubota, N. and K. Nishida, 2006. Prediction of human behavior patterns based on spiking neurons. Proceeding of the 15th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN06). Hatfield, UK.
   
7. Li, W. and W. Mingzhe, 2009. Extraction and confirmation of rules for human decision making. Proceeding of IEEE International Forum on Information Technology and Applications (IFITA’09), pp: 643-647.
   CrossRef    
8. Liu, F., M. Yang and P. Shi, 2008. Verification and validation of fuzzy rules-based human behavior models. Proceeding of 7th International Conference on System Simulation and Scientific Computing (ICSC, 2008) Asia Simulation Conference, pp: 813-819.
   PMCid:PMC2531274    
9. Lokman, J., J. Imai and M. Kaneko, 2008. Understanding human action in daily life scene based on action decomposition using dictionary terms and Bayesian network. Proceeding of IEEE 2nd International Symposium on Universal Communication (ISUC’08), pp: 67-74.
   CrossRef    
10. McNally, B.H., 2005. An approach to human behavior modeling in an air force simulation. Proceeding of Winter Simulation Conference. Orlando, pp: 1118-1122.
    CrossRef    
11. Meseguer, P., 1992. Incremental verification of rule-based expert systems. Proceeding of European Conference on Artificial Intelligence, pp: 840-844.
    
12. Mintzberg, H., 1989. Mintzberg on Management. 3rd Edn., Free Press, New York.
    
13. Murata, T., 1989. Petri nets: Properties, analysis and applications. P. IEEE, l7(4): 541-580.
    
14. Okuda, H., S. Hayakawa, T. Suzuki and N. Tsuchida, 2007. Modeling of human behavior in man-machine cooperative system based on hybrid system framework. Proceeding of IEEE International Conference on Robotics and Automation. Roma, Italy, pp: 10-14.
    CrossRef    
15. Schermerhorn, J.R., J.G. Hunt and R.N. Osborn, 2003. Core Concepts of Organizational Behavior. 3rd Edn., John Wiley and Sons, New York.
    
16. Shen, V.R.L., 2006. Knowledge representation using high-level fuzzy Petri nets. IEEE T. Syst. Man Cy. A, 36(6): 1220-1227.
    CrossRef    
17. Shiu, S.C.K., J.N.K. Liu and D.S. Yeung, 1996. An approach towards the verification of fuzzy hybrid rule/frame-based expert systems. Proceeding of 12th European Conference on Artificial Intelligence. John Wiley and Sons, Ltd.
    
18. Tousset, M., 1988. On the consistency of knowledge bases: The COVADIS system. Proceeding of European Conference on Artificial Intelligence, pp: 79-84.
    
19. Yang, S.J.H., J.J.P. Tsai and C. Chen, 2003. Fuzzy rule base systems verification using high-level Petri nets. IEEE T. Knowl. Data En., 15(2): 457-473.
    CrossRef    
20. Zhang, H., L. Rui and S. Jizhou, 2006. An emotional model for nonverbal communication based on fuzzy dynamic Bayesian network. Proceeding of Canadian Conference on Electrical and Computer Engineering, pp: 1534-1537.
    
21. Zhuomin, S., 2007. Multi-agent based modeling: methods and techniques for investigating human behaviors. Proceeding of the IEEE International Conference on Mechatronics and Automation. Harbin, China.
    

Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.