Fuzzy Logic Is Not Fuzzy: World-renowned Computer Scientist Lotfi A. Zadeh

In 1965 Lotfi A. Zadeh published "Fuzzy Sets", his pioneering and controversialpaper, that now reaches almost 100,000 citations. All Zadeh’s papers were citedover 185,000 times. Starting from the ideas presented in that paper, Zadeh foundedlater the Fuzzy Logic theory, that proved to have useful applications, from consumerto industrial intelligent products. We are presenting general aspects of Zadeh’s contributionsto the development of Soft Computing(SC) and Artificial Intelligence(AI),and also his important and early influence in the world and in Romania. Severalearly contributions in fuzzy sets theory were published by Romanian scientists, suchas: Grigore C. Moisil (1968), Constantin V. Negoita & Dan A. Ralescu (1974), DanButnariu (1978). In this review we refer the papers published in "From Natural Languageto Soft Computing: New Paradigms in Artificial Intelligence" (2008, Eds.: L.A.Zadeh, D. Tufis, F.G. Filip, I. Dzitac), and also from the two special issues (SI) of theInternational Journal of Computers Communications & Control (IJCCC, founded in2006 by I. Dzitac, F.G. Filip & M.J. Manolescu; L.A. Zadeh joined in 2008 to editorialboard). In these two SI, dedicated to the 90th birthday of Lotfi A. Zadeh (2011), andto the 50th anniversary of "Fuzzy Sets" (2015), were published some papers authoredby scientists from Algeria, Belgium, Canada, Chile, China, Hungary, Greece, Germany,Japan, Lithuania, Mexico, Pakistan, Romania, Saudi Arabia, Serbia, Spain,Taiwan, UK and USA.

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A Multicriteria Intelligence Aid Methodology Using MCDA, Artificial Intelligence, and Fuzzy Sets Theory

Mathematical Problems in Engineering ◽

10.1155/2017/9281321 ◽

2017 ◽

Vol 2017 ◽

pp. 1-10

Author(s):

Anissa Frini

Keyword(s):

Artificial Intelligence ◽

Fuzzy Sets ◽

Risk Attitude ◽

Multicriteria Decision Aid ◽

Intelligence Analysis ◽

Fuzzy Sets Theory ◽

Imperfect Data ◽

Business Executives ◽

Relevant Today ◽

Sets Theory

Intelligence is increasingly relevant today in both military and business intelligence contexts. Business executives, military, and governments have more large datasets and meet difficulties in anticipating threat/competitor future decisions. Decision anticipation is desirable because it will enhance situation understanding and then will limit the surprise effect and favor more appropriate reactions and decision-making. Generating and evaluating competitor/threat actions is a very challenging problem because of the uncertainty, incompleteness, and ambiguity associated with it. This paper extends the multicriteria decision aid (MCDA) methodology to the context of intelligence analysis and proposes the main pillars of a novel methodology called “Multicriteria Intelligence Aid” (MCIA). More specifically, this paper addresses how can we adapt MCDA to the context of intelligence analysis and how can we use existent methods and techniques from MCDA, artificial intelligence, and fuzzy sets theory to build this methodology. The paper presents the MCIA steps, which consist of (i) structuring the competitor/threat decision problem, (ii) handling imperfect data, (iii) modeling the analyst’s risk attitude, and (iv) aggregating the performance of the generated potential actions. An illustration of the methodology is provided in the military context. Results show that the novel methodology is applicable and provides interesting and valuable results.

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Zadeh's Centenary

International Journal of Computers Communications & Control ◽

10.15837/ijccc.2021.1.4102 ◽

2021 ◽

Vol 16 (1) ◽

Author(s):

Ioan DZITAC

Keyword(s):

Artificial Intelligence ◽

Fuzzy Logic ◽

Fuzzy Sets ◽

Soft Computing ◽

Special Issue ◽

Introductory Paper ◽

And Control

This is the introductory paper in a special issue on fuzzy logic dedicated to the centenary of the birth of Lotfi A. Zadeh published by International Journal of Computers Communications & Control (IJCCC). In 1965, Lotfi A. Zadeh published in the journal „Information and Control” the article titled „Fuzzy sets”, which today reaches over 117 thousand citations. The total sum of citations for all his papers is above 253 thousand. Based on the notion of fuzzy sets, fuzzy logic and the concept of soft computing emerged, bringing extremely important implications to the field of Artificial Intelligence (AI). In 2017, I published, whith F.G. Filip and M.J. Manolescu, a 42-page long paper in the IJCCC about the life and masterwork of Lotfi A. Zadeh, from which I will use some information in this material [15].

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Psychological Well-Being in Adolescence: An Approach from Fuzzy Sets Theory

PsycEXTRA Dataset ◽

10.1037/e534572010-001 ◽

2010 ◽

Author(s):

Monica Gonzalez ◽

Ferran Casas

Keyword(s):

Fuzzy Sets ◽

Well Being ◽

Fuzzy Sets Theory ◽

Psychological Well Being ◽

Sets Theory

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Faculty Opinions recommendation of Fuzzy sets and fuzzy logic in multi-criteria decision making. The 50th anniversary of Prof. Lotfi Zadeh's theory: introduction.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.726229734.793516038 ◽

2016 ◽

Author(s):

Shripad Tuljapurkar

Keyword(s):

Decision Making ◽

Fuzzy Logic ◽

Fuzzy Sets ◽

50Th Anniversary ◽

Multi Criteria Decision Making

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Condition Assessment Framework for Facility Management Based on Fuzzy Sets Theory

Buildings ◽

10.3390/buildings11040156 ◽

2021 ◽

Vol 11 (4) ◽

pp. 156

Author(s):

Deniz Besiktepe ◽

Mehmet E. Ozbek ◽

Rebecca A. Atadero

Keyword(s):

Fuzzy Sets ◽

Condition Index ◽

Condition Assessment ◽

Facility Management ◽

Maintenance Management ◽

Fuzzy Sets Theory ◽

Mean Time Between Failures ◽

Condition Rating ◽

Computerized Maintenance Management System ◽

Sets Theory

Condition information is essential to develop effective facility management (FM) strategies. Visual inspections and walk-through surveys are common practices of condition assessment (CA), generally resulting in qualitative and subjective outcomes such as “poor”, “good”, etc. Furthermore, limited resources of the FM process demand that CA practices be efficient. Given these, the purpose of this study is to develop a resource efficient quantitative CA framework that can be less subjective in establishing a condition rating. The condition variables of the study—mean time between failures, age-based obsolescence, facility condition index, occupant feedback, and preventive maintenance cycle—are identified through different sources, such as a computerized maintenance management system, expert opinions, occupants, and industry standards. These variables provide proxy measures for determining the condition of equipment with the implementation example for heating, ventilating, and air conditioning equipment. Fuzzy sets theory is utilized to obtain a quantitative condition rating while minimizing subjectivity, as fuzzy sets theory deals with imprecise, uncertain, and ambiguous judgments with membership relations. The proposed CA framework does not require additional resources, and the obtained condition rating value supports decision-making for building maintenance management and strategic planning in FM, with a comprehensive and less subjective understanding of condition.

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