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Wyszukujesz frazę "fuzzy rule" wg kryterium: Temat


Wyświetlanie 1-2 z 2
Tytuł:
Method of identifying a type 2 membership function and application to decision-making problems
Autorzy:
Uemura, Y.
Powiązania:
https://bibliotekanauki.pl/articles/970059.pdf
Data publikacji:
2015
Wydawca:
Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:
type 2 membership function
fuzzy linear regression model
fuzzy log-linear regression model
fuzzy linear polynomial regression model
indifferent zone
decision rule on a fuzzy event
Opis:
Tanaka (1991) suggested that the parameters of a linear regression model should be made fuzzy In order to better reflect the nature of the system, involving a definite degree of variability, and created a fuzzy linear regression model. This model can be formulated in the form of a linear programming problem that minimizes the span between the upper and lower limits under the constraints that include all data. In recent years, all the attention in this context has been focused on a fuzzy number that has an indifferent zone. A fuzzy number that we consider here is defined by using a type 2 membership function. This paper addresses the fact that a type 2 membership function has the upper and lower limits and shows that a type 2 membership function can be identified by expanding a fuzzy linear regression model into a fuzzy linear polynomial regression model. Finally, after a proposed fuzzy polynomial model is identified, a mathematical model is developed for a fuzzy decision-making method that accounts for an indifferent zone.
Źródło:
Control and Cybernetics; 2015, 44, 3; 399-406
0324-8569
Pojawia się w:
Control and Cybernetics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Learning of rule importance for fuzzy controllers to deal with inconsistent rules and for rule elimination
Autorzy:
Pal, K.
Pal, N.
Powiązania:
https://bibliotekanauki.pl/articles/205627.pdf
Data publikacji:
1998
Wydawca:
Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:
sterownik rozmyty
wartość reguły
wybór reguły
fuzzy logic controllers
rule importance
rule selection
rule tuning
Opis:
Extraction of correct and precise rules from experts is a difficult problem. Moreover, even when the extracted rules are correct, all of them may not have equal importance to achieve the goal of the fuzzy system. Rule tuning is usually achieved through modification of membership functions. Effect of changing a membership function is global in the sense, it influences all rules that involve the membership function. Here we propose an effective extension of the ordinary fuzzy controller model which incorpotates an importance factor for each rule. The importance factor allows tuning of the system at the rule level. Of course, one can still tune the membership functions. The extended model enables us to cope with incorrect and/or incompatibile rules and thereby enhances the robustness, flexibility and system modeling capability. It also helps us to eliminate redundant rules easily. For the Takagi-Sugeno framework, we derive the learning algorithm for the rule importance factor as well as that for the consequent. We demonstrate the superiority of the extended model through extensive simulation results using the inverted pendulum.
Źródło:
Control and Cybernetics; 1998, 27, 4; 521-543
0324-8569
Pojawia się w:
Control and Cybernetics
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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