Risk Assessment of Natural Disasters Using Fuzzy Logic System of Type 2

Authors

  • Dragan S Pamučar University of Defense in Belgrade, Military Academy, Serbia
  • Darko Božanić University of defence in Belgrade
  • Nenad Komazec University of Defence in Belgrade

DOI:

https://doi.org/10.7595/management.fon.2016.0016

Keywords:

fuzzy logic, interval fuzzy number, fuzzy logic system type 2, risk assessment, natural disasters

Abstract

Risk assessment of natural and other disasters in the Republic of Serbia is defined using special methodology. This paper presents a model of improving the existing methodology by using a new generation of fuzzy logic systems (fuzzy logic systems of type 2). This type of fuzzy logic systems is a significant improvement of the existing fuzzy logic systems of type 1. Fuzzy logic systems type 2 are based on the application of new interval fuzzy numbers that consider undetermined relative to classic fuzzy numbers in a better way. The fuzzy logic system presented in this paper translates vagueness and uncertainty, those that accompany risk assessment of natural disasters and other catastrophes, into an algorithm. This kind of algorithm makes the difference between data that are absolutely correct and those less accurate, those that clearly fit in the defined evaluation scales and those that are on the limit of values and so on. This kind of a model can help decisionmakers who conduct risk assessment of natural and other disasters since it is rather easy to use and does not require prior knowledge. Thereby, the existing methodology is used as a cornerstone in the developed model. Also, the model is significant for persons engaged in decision-making in other areas because it is a method that has not been extensively applied in science and practice, and whose development is at the beginning.

Author Biographies

Dragan S Pamučar, University of Defense in Belgrade, Military Academy, Serbia

Dragan S. Pamučar was born in Rijeka, Croatia. He earned his BS degree from the Technical Military Academy in Belgrade in 2003 and his MS degree from the Faculty of Transport and Traffic Engineering in Belgrade in 2009. He earned his PhD degree from the University of Defence in Belgrade, Department of Logistics, in 2013. His main research interests include Organization Design, Fuzzy Logic, Genetic algorithms, Neural
nets, Multicriteria Decision Making Models, Rough sets, etc. He is an assistant professor at the University of Defence in Belgrade, Department of Logistics, teaching Operations Research and Organization in Transport. He has published several academic articles or papers in international journals, including Yugoslav journal of operations research, Asia-Pacific Journal of Operational Research, Economic computation and economic cybernetics studies and research, Environmental impact assessment review, Expert systems with applications.

Darko Božanić, University of defence in Belgrade

Darko Božanić works at the Military Academy. He earned his BS degree from the Military Academy in Belgrade in 1999 and his MS degree from the Faculty of Political Sciences in Belgrade in 2011. He is currently a Ph.D. student at the Military Academy, University of Defence in Belgrade. His areas of interest include: energy security, multicriteria decision making and defense management.

Nenad Komazec, University of Defence in Belgrade

Nenad Komazec works at the Military Academy. He earned his BS degree from the Military Academy in Belgrade in 1996 and his MS degree from the Faculty of Security in Belgrade in 2006. He is currently a Ph.D. student at the Military Academy, University of Defence in Belgrade. His areas of interest include: risk management, protection and rescue and security management.



Published

2017-05-19

How to Cite

Pamučar, D. S., Božanić, D., & Komazec, N. (2017). Risk Assessment of Natural Disasters Using Fuzzy Logic System of Type 2. Management:Journal of Sustainable Business and Management Solutions in Emerging Economies, 21(80), 23–34. https://doi.org/10.7595/management.fon.2016.0016

Issue

Section

Articles

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