Advances in Fuzzy Decision Making: Theory and Practice by Iwona Skalna, Bogdan Rębiasz, Bartlomiej Gawel, Beata

By Iwona Skalna, Bogdan Rębiasz, Bartlomiej Gawel, Beata Basiura, Jerzy Duda, Janusz Opila, Tomasz Pelech-Pilichowski

This ebook exhibits how universal operation administration tools and algorithms might be prolonged to accommodate obscure or obscure details in decision-making difficulties. It describes tips on how to mix choice bushes, clustering, multi-attribute decision-making algorithms and Monte Carlo Simulation with the mathematical description of vague or imprecise info, and the way to imagine such info. additionally, it discusses a wide spectrum of real-life administration difficulties together with forecasting the plain intake of metal items, making plans and scheduling of construction approaches, undertaking portfolio choice and economic-risk estimation. it's a concise, but finished, reference resource for researchers in decision-making and decision-makers in enterprise corporations alike.

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22. Yager, R. 1981. A procedure for ordering fuzzy subsets of the unit interval. Information Sciences 24(2): 143–161. 23. Saneifard, R. 2009. Ranking L-R fuzzy numbers with weighted averaging based on levels. International Journal of Industrial Mathematics 1(2): 163–173. 24. , and A. Mert. 2007. On methods of defuzzification of parametrically represented fuzzy numbers. Automatic Control and Computer Sciences 41(5): 163–173. 25. , Z. Zhenfu, and L. Qi. 2006. Ranking fuzzy numbers with an area method using radius of gyration.

Sanchez, 59–66. Amsterdam: North Holland. 11. , and H. Prade. 1981. Triangular norms for fuzzy sets. In International symposium of fuzzy sets, 39–68, Linz. References 25 12. P. 1985. Selecting uncertainty calculi and granularity: An experiment in trading off precision and complexity. In Proceedings of the first Workshop on Uncertainty in Artificial Intelligence, 57–66, Los Angeles. 13. A. 1975. In Fuzzy sets and their applications to cognitive and decision processes, ed. -S. Fu, K. Tanaka, and M.

28. -W. Lu. 2001. An approximate approach for ranking fuzzy numbers based on left and right dominance. Computers and Mathematics with Applications 41(12): 1589–1602. 29. , and D. Filev. 1999. On ranking fuzzy numbers using valuations. International Journal of Intelligent Systems 14(12): 1249–1268. Chapter 3 Fuzzy Random Variable and the Dempster-Shafer Theory of Evidence Abstract This chapter presents the concept of uncertainty propagation in real world desicion problems, where some input parameters are stochastic while information about others is partial and is represented by fuzzy random variable.

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