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FORECASTING IN FUZZY SYSTEMS [PDF]

International Journal of Information Technology & Decision Making, 2011
Fuzzy regression has been applied to marketing, management, and sales forecasting for many years. In this paper, two types of forecasting methods within the framework of fuzzy regression analysis are discussed. The first type is a conventional forecasting method, which intends to find the value of a dependent variable when the given values of ...
HSIAO-FAN WANG, RUEY-CHYN TSAUR
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Probabilistic Fuzzy Systems as Additive Fuzzy Systems

2014
Probabilistic fuzzy systems combine a linguistic description of the system behaviour with statistical properties of data. It was originally derived based on Zadeh’s concept of probability of a fuzzy event. Two possible and equivalent additive reasoning schemes were proposed, that lead to the estimation of the output’s conditional probability density ...
Rui Jorge Almeida, Nick Verbeek, Uzay Kaymak, João Miguel da Costa Sousa   +3 more
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Fuzzy systems and approximation

Fuzzy Sets and Systems, 1997
Abstract The basic motivation of using fuzzy rule-based systems especially for control purposes is to deduce simple and fast approximations of the unknown or too complicated models. Fuzzy rule-based systems have become very popuar because of their transparency and easiness of tuning and modification.
Zorat, Alessandro, L. Koczy
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Fuzzy systems

Communications of the ACM, 1994
Born in the United States around 1965, fuzzy set theory has grown to become a major scientific domain collectively referred to in this article as «fuzzy systems,» which include fuzzy sets, logic, algorithms, and control. For the past few years, particularly in japan, approximately 1,000 commercial and industrial fuzzy systems have been successfully ...
Toshinori Munakata, Yashvant Jani
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On the general theory of fuzzy systems: Fuzzy linearity and fuzzy dynamic systems

Journal of Computer and Systems Sciences International, 2008
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Kozhukhar, V. A., Pushkov, S. G.
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Improving the fuzzy system performance by fuzzy system ensemble

Fuzzy Sets and Systems, 1998
This paper proposes a fuzzy system ensemble (FSE) that can improve the system performance in non-linear and complex problems. Each fuzzy system in the FSE is built from two design stages, each stage of which is performed by different genetic algorithms (GAs).
Kim, D
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Fuzzy stopping of a dynamic fuzzy system

1998 Second International Conference. Knowledge-Based Intelligent Electronic Systems. Proceedings KES'98 (Cat. No.98EX111), 2002
This paper discusses an optimal stopping problem of fuzzy systems with fuzzy rewards in a class of fuzzy stopping times, which are extended from usual stopping times. Some properties regarding the optimal fuzzy stopping times are presented.
Masami Kurano, Masami Yasuda, Jun-ichi Nakagami, Yuji Yoshida   +3 more
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Fuzzy systems

Soft Computing, 2005
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Fuzzy L-systems

International Journal of Computer Mathematics, 1990
Fuzzy L-systems are presented as a formal mechanism for generating fuzzy formal languages. This provides a mechanism for modelling development while also incorporating the vagueness inherent to most real world processes. In this paper, fuzzy L-systems are defined, a normal form is developed, closure properties of fuzzy L-systems—both language-theoretic
M. V. Nagendra Prasad, Meena Mahajan, Kamala Krithivasan   +2 more
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