Results 301 to 310 of about 164,645 (346)

Inference with Fuzzy and Probabilistic Information

2010
In the paper we deal with fuzzy sets under the interpretation given in a coherent probabilistic setting. We provide a general Bayesian inference process involving fuzzy and partial probabilistic information by showing its peculiarities.
Giulianella Coletti, Barbara Vantaggi
openaire   +3 more sources

Well Correlation by Fuzzy Inference

11th International Congress of the Brazilian Geophysical Society & EXPOGEF 2009, Salvador, Bahia, Brazil, 24-28 August 2009, 2009
Well correlation performed using the interpretation of patterns present in wireline logs tries to establish lateral extension and variations in the reservoir parameters from one borehole to another. In the other hand, stratigraphic correlation aims to produce a cross-section of an oil field based on facies recognition using outcrops or cores and the ...
Carolina Barros, André Andrade
openaire   +1 more source

GA with fuzzy inference system

Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512), 2002
Applications of genetic algorithms (GA) for optimisation problems are widely known as well as their advantages and disadvantages compared with classical numerical methods. In practical tests, GA appears a robust method with a broad range of applications. The determination of GA parameters could be complicated. Therefore for some real-life applications,
Radomil Matousek, Pavel Osmera, Jan Roupec   +2 more
openaire   +1 more source

Fuzzy inference neural network

Neurocomputing, 1997
Abstract A new model for the design of Fuzzy Inference Neural Network (FINN) is proposed in this paper. It can automatically partition an input-output pattern space and can extract fuzzy if-then rules from numerical data. The proposed FINN is a two-layer network which utilizes Kohonen's algorithm.
Takatoshi Nishima, Masafumi Hagiwara
openaire   +1 more source

Fuzzy Inference Network with Mamdani Fuzzy Inference System

2018
In the modern era, the amount of data generated is increasing at an exponential rate. The generated data has both numeric as well as linguistic form. Learning or extracting relevant information from these types of data is a major challenge for researchers.
Nishchal K. Verma, Vikas Singh, Shreedharkumar Rajurkar, Mohd Aqib   +3 more
openaire   +1 more source

Parallel processing of fuzzy inferences

Proceedings of 24th International Symposium on Multiple-Valued Logic (ISMVL'94), 2002
Rule based systems are computationally very demanding, since a large number of rules has to be evaluated every time new input data are observed in order to undertake a corresponding action. The authors study the possible improvements in performance by using parallel processing.
Claudio Moraga, Javier Cañas, Raúl Monge, Luis Salinas, Manuel Gómez   +4 more
openaire   +1 more source

Inference with Probabilistic and Fuzzy Information

2013
We adopt the interpretation of fuzzy sets in terms of coherent conditional probabilities, introduced in [2–4] and presented in this issue [7] by R. Scozzafava. Aim of this chapter is to discuss (from a syntactical point of view) which concepts of fuzzy sets theory [9] are naturally obtained simply by using coherence.
COLETTI, Giulianella, B. Vantaggi
openaire   +1 more source

Fuzzy functional inference method

International Conference on Fuzzy Systems, 2010
This paper proposes a fuzzy functional inference method in which the consequent parts of the T-S inference method is generalized to fuzzy functions. Moreover, this paper addresses equivalence of the proposed fuzzy inference method. Namely, the fuzzy functional inference method is shown to be equivalent to the weighted T-S inference method whose ...
Hirosato Seki, Masaharu Mizumoto
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Fuzzy Inference and Fuzzy Control

2009
The major subject of this chapter is fuzzy control, one of the most successful application areas of fuzzy set theory. Nowadays, many fuzzy products are visible in the market. Almost every fuzzy product is related to a fuzzy control problem. It is no exaggeration to say that fuzzy set theory is highly accepted partly because of the great success of ...
Xuzhu Wang, Da Ruan, Etienne E. Kerre
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On Liu’s Inference Rules for Fuzzy Inference Systems

2010
Liu’s inference is a process of deriving consequences from fuzzy knowledge or evidence via the tool of conditional credibility. Using membership functions, this paper derives some expressions of Liu’s inference rule for fuzzy systems. This paper also gives some new inference rules with multiple antecedents and with multiple if-then rules.
Xin Gao, Dan A. Ralescu, Yuan Gao
openaire   +1 more source