K. Hirota and M. Sugeno, Eds., Industrial Applications of Fuzzy Technology in the World. World Scientific, 1995. Home/Search Document Not in Database Summary Related Articles Check |
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Application Of Knowledge Based Systems For Supervision.. - Haber, Haber, Alique.. (Correct)
....Logic (FL) is one such intelligent technique, and it has proven useful in control and industrial engineering as a very practical optimizing tool. The growing number of successful industrial applications of fuzzy logic worldwide really provides the best credentials the technique could hope for [40,56]. FL can be used to build process models on the basis of the expertise of experienced human operators. Also, through FL supervisory and control systems can be invested with the verbally expressed experience of a trained operator. Through FL we can plug human knowledge, expressed in qualitative ....
K. Hirota and M. Sugeno, Industrial applications of fuzzy technology in the world, Advances in Fuzzy Systems Applications and Theory 2, Singapore, World Scientific, 1995.
Multi-Resolution Techniques in the Rules-Based.. - Yam, Nguyen, Kreinovich (1999) (Correct)
....in terms of natural language, like small ) into a precise control strategy. During the 25 years of its existence, it has led to many spectacular applications, ranging from appliances to automatic subway control to superprecise temperature control on a Space Shuttle mission (see, e.g. [8, 9]) The fact that intelligent control is a reasonable strategy is emphasized by the results that every possible control strategy can be, within an arbitrary accuracy, approximated by a fuzzy controller (for a recent survey of such results, see, e.g. 16, 26] The problem with this approach is ....
K. Hirota and M. Sugeno, "Industrial Applications of Fuzzy Technology in the World", World Scientific, Singapore, 1996.
Computational Complexity and Feasibility of Fuzzy.. - Nguyen, Koshelev, .. (1997) (Correct)
....: n (xn ) for each such tuple, and then ffl find the largest of these values, then the only way to minimize the computation time is to minimize the time spent on computing , i.e. use min. However, for fuzzy numbers, many faster methods of computing (1) are known, see, e.g. 26] 12] [6], 15] 16] With these indirect faster methods, it may happen that minimum no longer leads to the fastest computations. It turns out that which t norm is the fastest depends on the function f(x 1 ; xn ) We will start our analysis by considering linear functions f(x 1 ; xn ) ....
K. Hirota and M. Sugeno, Industrial Applications of Fuzzy Technology in the World, World Scientific, Singapore, 1996.
The Fuzzy Ant - Valeri Rozin And (Correct)
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K. Hirota and M. Sugeno, Eds., Industrial Applications of Fuzzy Technology in the World. World Scientific, 1995.
On the Possibility of Using Complex Values in Fuzzy.. - Nguyen, Kreinovich.. (1996) (Correct)
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Hirota, K., and Sugeno, M., Industrial Applications of Fuzzy Technology in the World, World Scientific, Singapore, 1996.
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