Unification of imprecise data - translation of fuzzy to multi-valued knowledge over Y-axis

2022 ◽  
Vol 11 (1) ◽  
pp. 0-0
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Numerical Study ◽  
Knowledge Based Systems ◽  
Membership Functions ◽  
Imprecise Data ◽  
Knowledge Based ◽  
Data Translation ◽  
Inference Systems ◽  
Expert Reasoning

Inference systems are a well-defined technology derived from knowledge-based systems. Their main purpose is to model and manage knowledge as well as expert reasoning to insure a relevant decision making while getting close to human induction. Although handled knowledge are usually imperfect, they may be treated using a non classical logic as fuzzy logic or symbolic multi-valued logic. Nonetheless, it is required sometimes to consider both fuzzy and symbolic multi-valued knowledge within the same knowledge-based system. For that, we propose in this paper an approach that is able to standardize fuzzy and symbolic multi-valued knowledge. We intend to convert fuzzy knowledge into symbolic type by projecting them over the Y-axis of their membership functions. Consequently, it becomes feasible working under a symbolic multi-valued context. Our approach provides to the expert more flexibility in modeling their knowledge regardless of their type. A numerical study is provided to illustrate the potential application of the proposed methodology.

scholarly journals Guest Editorial

1997 ◽  
Vol 12 (3) ◽  
pp. 229-230 ◽  
Author(s):  
DAVE STUART ROBERTSON
Keyword(s):  
Fuzzy Logic ◽  
Decision Support ◽  
World Wide ◽  
Guest Editorial ◽  
Human Life ◽  
Knowledge Based Systems ◽  
Fuzzy Logic Controllers ◽  
Incorrect Decision ◽  
Knowledge Based ◽  
The World

Knowledge based systems are used in applications where an incorrect decision could put human life in jeopardy. A quick trawl through the World Wide Web is sufficient, these days, to locate such applications in design, analysis and testing; protection advice; operator decision support; signal monitoring; embedded systems and others. Depending on the type of system, these either give information which is not guaranteed to be correct (in many operator support applications) or which is imprecise (for example in fuzzy logic controllers).

scholarly journals Optimization Model of Fuzzy Rule Based Expert System Using Max-Min Composition and Schema Mapping Translation

INSIST ◽  
2017 ◽  
Vol 2 (1) ◽  
pp. 30 ◽  
Author(s):  
Hartono Hartono ◽  
Tiarma Simanihuruk
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Expert System ◽  
Membership Function ◽  
Fuzzy Rule ◽  
Fuzzy Decision Making ◽  
Schema Mapping ◽  
Fuzzy Decision ◽  
Rule Based ◽  
Knowledge Based

Abstract— Fuzzy Decision Making involves a process of selecting one or more alternatives or solutions from a finite set of alternatives which suits a set of constraints. In the rule-based expert system, the terms following in the decision making is using knowledge based and the IF Statements of the rule are called the premises, while the THEN part of the rule is called conclusion. Membership function and knowledge based determines the performance of fuzzy rule based expert system. Membership function determines the performance of fuzzy logic as it relates to represent fuzzy set in a computer. Knowledge Based in the other side relates to capturing human cognitive and judgemental processes, such as thinking and reasoning. In this paper, we have proposed a method by using Max-Min Composition combined with Genetic Algorithm for determining membership function of Fuzzy Logic and Schema Mapping Translation for the rules assignment.Keywords— Fuzzy Decision Making, Rule-Based Expert System, Membership Function, Knowledge Based, Max-Min Composition, Schema Mapping Translation

scholarly journals Application of fuzzy logic at the Port of Cotonou (Benin / West Africa) in analysis of port logistics viability

2021 ◽  
Vol 9 (2) ◽  
pp. 209-225
Author(s):  
Alphonse Hounsounou ◽  
Prof. Dr. Hito Braga de Moraes ◽  
Prof. Dr. Maamar El Robrini
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
West Africa ◽  
Membership Functions ◽  
Medium Term ◽  
Matlab Toolbox ◽  
Access Channel ◽  
Port Logistics ◽  
Input Variables

The Autonomous Port of Cotonou (PAC) located in West Africa has an access channel 15m deep, 11 berths, and an internal draft of 15m (maximum), and is connected with a road to serve continental countries such as Burkina-Faso, Chad , Mali, Niger and Nigeria. The PAC presents low productivity (average of 10,000,000 tons / year, 24.40% of the movement from the port of Lagos / Nigeria) in West Africa. This article aims to evaluate the application of fuzzy logic in the Autonomous Port of Cotonou (Benin) in the analysis of logistic viability. The methodology followed the fuzzy logic that is a support method for logistic decision-making, based on fuzzy rules (SBRF). It was used characteristic of Mamdani Matlab Toolbox with three membership functions (triangular, trapezoidal and Gaussian) to model the quality variables of infrastructures and services, equipment productivity, seeking a long-term way out of logistic viability. The result of logistic viability was medium term, equivalent to 13 years / 25 years; as far as the outcome of the future PAC is concerned. The logistic viability of the PAC depends on its input variables. The projection of this application was long term, at least 19 years / 25 years when the infrastructures are of good quality and the equipment is more modern and consistent with the current realities to satisfy the expectations of the customers.  

Decision-Making Support Systems

2005 ◽  
pp. 759-765 ◽  
Author(s):  
Guisseppi Forgionne ◽  
Manuel Mora ◽  
Jatinder N.D. Gupta ◽  
Ovsei Gelman
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Information Systems ◽  
Support Systems ◽  
Decision Makers ◽  
Knowledge Based Systems ◽  
Executive Information Systems ◽  
Knowledge Based ◽  
Computer Based ◽  
Decision Making Support

Decision-making support systems (DMSS) are specialized computer-based information systems designed to support some, several or all phases of the decision-making process (Forgionne et al., 2000). They have the stand-alone or integrated capabilities of decision support systems (DSS), executive information systems (EIS) and expert systems/knowledge based systems (ES/KBS). Individual EIS, DSS, and ES/KBS, or pair-integrated combinations of these systems, have yielded substantial benefits for decision makers in real applications.

Analysis of New Aggregation Operators: Mean 3Π

2007 ◽  
Vol 11 (6) ◽  
pp. 561-569 ◽  
Author(s):  
Andrei Doncescu ◽  
◽  
Sebastien Regis ◽  
Katsumi Inoue ◽  
Richard Emilion ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Aggregation Operators ◽  
Mathematical Form ◽  
Knowledge Based Systems ◽  
Sources Of Information ◽  
Knowledge Based ◽  
Many Sources ◽  
Robust To Noise

Knowledge based systems need to deal with aggregation and fusion of data with uncertainty. To use many sources of information in numerical forms for the purpose of decision or conclusion, systems suppose to have tools able to represent the knowledge in a mathematical form. One of the solutions is to use fuzzy logic operators. We present in this article an improvement of the triple Π operator introduced by Yager and Rybalov, which is calledmean3Π. Whereas triple Π is an operator completely reinforced, the presented operator is a mean operator, which makes it more robust to noise.

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