Intelligent factories using fuzzy expert systems

Lee, Edward T.

doi:10.1108/03684929610116428

Cited by 15 publications

(3 citation statements)

References 10 publications

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“…The results obtained in this paper may have useful applications in robot vision interpretation, picture description (Lee, 1988), visual languages (Chang, 1986), pattern recognition (Lee et al, 1987b), robotics (Staugaard, 1987) and artificial intelligence, model parallel computers, software engineering (Bell et al, 1987;Sommerville, 1982), medical expert systems (Lee, 1996(Lee, , 1999Lee and Lee, 1996;Keller, 1987;Waterman, 1986), and fuzzy logic functions (Lee, 1993;Chou, 1995, 2001;Lee and Lee 1975).…”

Section: Discussionmentioning

confidence: 81%

Line‐oriented two‐dimensional parallel computer languages

Lee

2002

Kybernetes

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Line-oriented two-dimensional grammars (LOTDGs), region-oriented two-dimensional grammars (ROTDGs) and parallel productions are introduced. The relationships between LOTDGs and ROTDGs are stated. Examples of LOTDGS for generating all possible 458 rightangled triangles, all possible squares, all possible 458 isosceles trapezoids, and all possible 458 parallelograms using parallel productions are presented. A new concise representation of a derivation chain is also introduced and illustrated by examples. LOTDGs and ROTDGs are compared. Generally speaking, LOTDGs require less terminal variables and non-terminal variables, require less storage space, and require less derivation steps. Seven challenging problems for future research are also included. In addition, parallel production is an effective tool to model parallel computers as well as parallel processing. The results have useful applications in robot vision interpretation, robot pictorial communication, artificial intelligence, visual languages, software engineering, medical expert systems, and fuzzy logic functions.

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Section: Discussionmentioning

confidence: 81%

Line‐oriented two‐dimensional parallel computer languages

Lee

2002

Kybernetes

Self Cite

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“…Applications to function representation, data compression, and error correction, are presented. The results may have useful applications in fuzzy logic, expert systems (Lee and Lee, 1996), fuzzy expert systems (Lee, 1996), and management of uncertainty (Zadeh, 1983).…”

Section: Discussionmentioning

confidence: 98%

Fuzzy monotone functions and applications

Lee

Chou

2001

Kybernetes

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The grade of membership function for fuzzy monotone functions is defined and investigated. An algorithm for finding the membership value is presented. A minterm even function and minterm odd function are defined and studied. It is found that these two functions are the two most alternation functions. The relationships with threshold functions are also presented. In addition, three ways to implement a fuzzy monotone increasing function are investigated. Applications to function representation, data compression and error detection are illustrated. The results have useful applications in fuzzy logic, expert systems, fuzzy expert systems, and also management of uncertainty.

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“…In fuzzy set theory based on fuzzy logic a particular object has a degree of membership in a given set that may be anywhere in the range of 0 (completely not in the set) to 1 (completely in the set) [4,5]. Besides that, fuzzy logic is a new way to program computers and appliances to mimic the imprecise way humans make decisions [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Students Performance using Fuzzy Set Theory in Online Learning of Islamic Finance Course

Bakar

Rosbi

Bakar

2021

Int. J. Interact. Mob. Technol.

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<p class="0abstract"><strong>Abstract—</strong>The objective of this study is to evaluate student performance using fuzzy set theory in Islamic Finance online course. This study focuses on selecting best individual among 30 students that registered for Islamic Bank Management course. The variables that involved in this study are online quiz marks, online assignment marks and online self-learning time. The outcome of the fuzzy set analysis was compared with final examination data. The methodology of this study involving converting real data to fuzzy set, intersection calculation, decision analysis using maximizing approach. Result of fuzzy set shows the best individual score is 0.9. This student selected as best candidate for student performance in online learning with considering three variables namely online quizzes, online assignment and online self-learning hour. The comparison with final examination marks shows a good agreement with fuzzy set theory that concluded best individual from fuzzy set theory exhibits highest performance during final examination. The main finding of this study can help educators to predict the best performer in online learning class. In the same time, finding of this study can act as guideline to advise students in achieving their desired grade for online learning course.</p>

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Intelligent factories using fuzzy expert systems

Abstract: Air conditioners: it allows electric coolers and heaters to change temperature, based on the number of people who are in the room, or the power requirement of a house.

Cited by 15 publications

References 10 publications

Line‐oriented two‐dimensional parallel computer languages

Line‐oriented two‐dimensional parallel computer languages

Fuzzy monotone functions and applications

Evaluation of Students Performance using Fuzzy Set Theory in Online Learning of Islamic Finance Course

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