Abstract
Fuzzy logic techniques were originally designed to translate expert knowledge—which is often formulated by using imprecise (“fuzzy”) from natural language (like “small”)—into precise computer-understandable models and control strategies. Such a translation is still the main use of fuzzy techniques. Lately, it turned out that fuzzy methods can help in another class of applied problems: namely, in situations when there are semi-heuristic techniques for solving the corresponding problems, i.e., techniques for which there is no convincing theoretical justification. Because of the lack of a theoretical justification, users are reluctant to use these techniques, since their previous empirical success does not guarantee that these techniques will work well on new problems. In this paper, we show that in many such situations, the desired theoretical justification can be obtained if, in addition to known (crisp) requirements on the desired solution, we also take into account requirements formulated by experts in natural-language terms. Naturally, we use fuzzy techniques to translate these imprecise requirements into precise terms.
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Acknowledgements
We are very thankful to the organizers of the 2016 World Conference on Soft Computing for their support, and to all the conference participants for their valuable suggestions. This work was also supported in part by the National Science Foundation grants HRD-0734825 and HRD-1242122 (Cyber-ShARE Center of Excellence) and DUE-0926721, by an award from Prudential Foundation, and by Chiang Mai University, Thailand.
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Kreinovich, V., Kosheleva, O., Dumrongpokaphan, T. (2018). Beyond Traditional Applications of Fuzzy Techniques: Main Idea and Case Studies. In: Zadeh, L., Yager, R., Shahbazova, S., Reformat, M., Kreinovich, V. (eds) Recent Developments and the New Direction in Soft-Computing Foundations and Applications. Studies in Fuzziness and Soft Computing, vol 361. Springer, Cham. https://doi.org/10.1007/978-3-319-75408-6_36
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DOI: https://doi.org/10.1007/978-3-319-75408-6_36
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