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Analysis of the operators involved in the definition of the implication functions and in the fuzzy inference process

I. Rojas, O. Valenzuela, M. Anguita, A. Prieto
1998 International Journal of Approximate Reasoning  
defuzzification method) involved in the definition of the implication function and in the rest of the inference process.  ...  This paper analyzes the performance of some fuzzy implications proposed in the bibliography together with the operators needed for their definition and for the fuzzy inference process, Examining the specialized  ...  In this paper the role and significance of the operators involved in the definition of the fuzzy implication operator and in the fuzzy inference process are investigated by using an appropriate statistical  ... 
doi:10.1016/s0888-613x(98)10016-6 fatcat:7caga3qsrreofnct4uzgcoxmy4

Fuzzy logic in control systems: fuzzy logic controller. II

C.C. Lee
1990 IEEE Transactions on Systems, Man and Cybernetics  
In particular, the exposition includes a discussion of fuzzification and defuzzification strategies, the derivation of the database and fuzzy control rules, the definition of fuzzy implication, and an  ...  During the past several years, fuzzy control has emerged as one of the most active and fruitful areas for research in the applications of fuzzy set theory, especially in the realm of industrial processes  ...  Definition 5: Fuzzy Implication: The fuzzy implication is associated with five families of fuzzy implication functions in use.  ... 
doi:10.1109/21.52552 fatcat:556g3vy64jhxvp43oerwww6ati

The enhancement of the cell-based GIS analyses with fuzzy processing capabilities

T YANAR, Z AKYUREK
2006 Information Sciences  
The operation of the proposed system is presented through case studies, which demonstrate its application for classification and decision-making processes.  ...  This thesis shows how fuzzy logic approach may contribute to a better representation and reasoning with imprecise concepts, which are inherent characteristics of geographic data stored and processed in  ...  Design of Fuzzy Inference Engine Operations of fuzzy sets, linguistic variable definitions, fuzzy if-then rules and fuzzy inference compose main functionality of the Fuzzy Inference Engine.  ... 
doi:10.1016/j.ins.2005.02.006 fatcat:etgbpgq76rec3c4hru5hw6fwty

Fuzzy logic in control systems: fuzzy logic controller. I

C.C. Lee
1990 IEEE Transactions on Systems, Man and Cybernetics  
In particular, our exposition includes a discussion of fuzzification and denazification stra tegies, the derivation of the database and fuzzy control rules, the definition of fuzzy implication, and an  ...  During the past several years, fuzzy control has emerged as one of the most active and fruitful areas for research in the applications of fuzzy set theory, especially in the realm of industrial processes  ...  inferring fuzzy control actions employing fuzzy implication and the rules of inference in fuzzy logic. [4] The defuzzification interface performs the following functions: (a) a scale mapping, which converts  ... 
doi:10.1109/21.52551 fatcat:56hot4lt6zbzbbhkualwwceveq

Page 5173 of Mathematical Reviews Vol. , Issue 99h [page]

1999 Mathematical Reviews  
[Prieto Espinosa, Alberto] (E-GRAN-AT; Granada) Analysis of the operators involved in the definition of the implication functions and in the fuzzy inference process. (English summary) Internat. J.  ...  de- fuzzification method) involved in the definition of the implication function and in the rest of the inference process.  ... 

Multidimensional sensitivity study of the fuzzy risk assessment module in the life cycle of building objects

Edyta Plebankiewicz, Damian Wieczorek
2018 Open Engineering  
The main purpose of this paper is to check the correctness of the operation of "the fuzzy risk assessment module in the life cycle of building objects".  ...  variables, rules of fuzzy implication to the process of aggregation of premises and aggregation of result conclusions, as well as methods for defuzzification the resultant value.  ...  The authors recommend that the risk evaluator, when using the fuzzy risk assessment module in the life cycle of building objects, apply either sets of basic or alternative membership functions I and II  ... 
doi:10.1515/eng-2018-0059 fatcat:2wiw3bps25c3pj4amkrpecvora

Page 4131 of Mathematical Reviews Vol. , Issue 92h [page]

1992 Mathematical Reviews  
The definitions of membership functions of fuzzy sets used in the reasoning process may, however, adversely affect the reasoning results if the ‘insignif- icant’ parts of the membership functions are incompatible  ...  It has been expected to provide a more powerful and useful inference capability in the process of fuzzy reasoning.  ... 

Fuzzy Logic Speech/Non-speech Discrimination for Noise Robust Speech Processing [chapter]

R. Culebras, J. Ramírez, J. M. Górriz, J. C. Segura
2006 Lecture Notes in Computer Science  
The fuzzy system is based on a Sugeno inference engine with membership functions defined as combination of two Gaussian functions.  ...  This paper shows a fuzzy logic speech/non-speech discrimination method for improving the performance of speech processing systems working in noise environments.  ...  Acknowledgements This work has been funded by the European Commission (HIWIRE, IST No. 507943) and the Spanish MEC project TEC2004-03829/FEDER.  ... 
doi:10.1007/11758501_55 fatcat:kbwkem3kjncrnixzaibswrszlq

IMPROVING INTERNAL-VALUED INFERENCING WITH LIKELIHOD RATIO

Lim Chee Kau
2019 Malaysian Journal of Computer Science  
As an improvement, a measurement on the likelihood of an inference result in an acceptance/rejection band suggested.  ...  This paper point out the limitations of Interval-Valued Inferencing as a defuzzification method for inference engines based on the Bandler-Kohout subproduct.  ...  operator in harsh criterion, or arithmetic mean in mean criterion, A(x) and B(x) are membership functions of x in A and B respectively, and → denotes the fuzzy implication operator.  ... 
doi:10.22452/mjcs.vol32no3.3 fatcat:gecngox5xfelpczw3z2hbrmcti

A Situation Analysis Decision Support System Based on Dynamic Object Oriented Bayesian Networks

Mohsen Naderpour, Jie Lu
2014 Journal of Software  
This paper proposes a situation analysis decision support system (SADSS) for safety of safety-critical systems where the operators are stressed by the task of understanding what is going on in the situation  ...  process by aiding operators' cognitive activities.  ...  Situation analysis processes are often distributed in nature and involve multiple operation operators that observe and react to events distributed in time and space, so the future direction of the research  ... 
doi:10.4304/jsw.9.8.2194-2199 fatcat:u2idkvffs5fpjmvuca7xvpbq5m

The fuzzy set theory approach to transportation problems

Shinya KIKUCHI
1993 Doboku Gakkai Ronbunshu  
It should be interesting to examine the implication of approximate numbers in the travel forecasting process using fuzzy arithmetic operations.  ...  -Reasoning and inference for the decision is based on the approximate logic, in which the implication is ambiguous due to the vagueness of the meaning of words and the lack of precise knowledge.  ... 
doi:10.2208/jscej.1993.1 fatcat:2vdcoahytjbhdjbsmvssam2syq

HyFOM Reasoner: Hybrid Integration of Fuzzy Ontology and Mamdani Reasoning
english

Cristiane A. Yaguinuma, Walter C. P. Magalhães Jr., Marilde Terezinha Prado Santos, Heloisa A. Camargo, Marek Reformat
2013 Proceedings of the 15th International Conference on Enterprise Information Systems  
In this context, the appropriate combination of fuzzy ontologies and Mamdani fuzzy inference systems can provide meaningful inferences involving fuzzy rules and numerical property values.  ...  A real-world case study involving the domain of food safety is presented, including comparative results with a state-of-the-art fuzzy description logic reasoner.  ...  Special thanks to the Embrapa Dairy Cattle and the Brazilian Ministry of Agriculture, Livestock and Supply for providing real-world data and domain expert support for the case study.  ... 
doi:10.5220/0004452803700378 dblp:conf/iceis/YaguinumaMSCR13 fatcat:yelpfdgpe5aqvjniya2qzoogoi

A MATHEMATICAL MODEL FOR WIRELINE LOGS FILTERING USING DIFFERENTIAL FUZZY PARAMETERS

Carlos Eduardo Guerra, André José Neves Andrade, Ivnon José de Farias Lima
2012 Revista Brasileira de Geofisica  
The objective of this study is to present a non-linear technique for noise attenuation in well logs using fuzzy sets and fuzzy logic.  ...  After acquisition, the processing depends on the nature of the signal and its information.  ...  ACKNOWLEDGMENTS We thank PETROBRAS, ANP and the Graduate Program in Geophysics at UFPA (CPGF) for supporting this work and providing data.  ... 
doi:10.22564/rbgf.v30i3.188 fatcat:godwcl5c5bdpteft2ca2qe2k4m

Regulation of water resources systems using fuzzy logic: a case study of Amaravathi dam

P. V. P. Moorthi, Ajit Pratap Singh, P. Agnivesh
2018 Applied Water Science  
The main motive of this study is to demonstrate applicability of fuzzy inference system for regulating operations of water resource systems.  ...  Regulation of a water resource system is one of the challenging tasks due to uncertainty involved in demand and supply.  ...  The process of arriving at inference and learning of the structure for a basic "if-then" rule-based system involves the application of "implication connective" between different proportions defined for  ... 
doi:10.1007/s13201-018-0777-8 fatcat:2zp7nccrevcjhfznjjvjummuai

PROPOSING A NEW METHODOLOGY BASED ON FUZZY LOGIC FOR TUNNELLING RISK ASSESSMENT

Abdolreza Yazdani-Chamzini
2014 Journal of Civil Engineering and Management  
and decisions in order to reduce, mitigate and/or even eliminate the risks involved in the project.  ...  In many situations, tunnelling projects find themselves involved in the situations where unexpected conditions threaten the continuity of the project.  ...  The process of fuzzy inference involves fuzzification of crisp input by defining the membership function, fuzzy logic operators, and IF-THEN rules (Beriha et al. 2012) .  ... 
doi:10.3846/13923730.2013.843583 fatcat:aniq2et34zfghkubbfpclpioqq
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