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

In 1965 Lotfi A. Zadeh published "Fuzzy Sets", his pioneering and controversial paper, that now reaches almost 100,000 citations. All Zadeh’s papers were cited over 185,000 times. Starting from the ideas presented in that paper, Zadeh founded later the Fuzzy Logic theory, that proved to have useful applications, from consumer to industrial intelligent products. We are presenting general aspects of Zadeh’s contributions to the development of Soft Computing(SC) and Artificial Intelligence(AI), and also his important and early influence in the world and in Romania. Several early contributions in fuzzy sets theory were published by Romanian scientists, such as: Grigore C. Moisil (1968), Constantin V. Negoita & Dan A. Ralescu (1974), Dan Butnariu (1978). In this review we refer the papers published in "From Natural Language to 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 the International Journal of Computers Communications & Control (IJCCC, founded in 2006 by I. Dzitac, F.G. Filip & M.J. Manolescu; L.A. Zadeh joined in 2008 to editorial board). In these two SI, dedicated to the 90th birthday of Lotfi A. Zadeh (2011), and to the 50th anniversary of "Fuzzy Sets" (2015), were published some papers authored by scientists from Algeria, Belgium, Canada, Chile, China, Hungary, Greece, Germany, Japan, Lithuania, Mexico, Pakistan, Romania, Saudi Arabia, Serbia, Spain, Taiwan, UK and USA

Special Libraries, Summer 1992

Volume 83, Issue 3https://scholarworks.sjsu.edu/sla_sl_1992/1002/thumbnail.jp

Summer Mustang, June 29, 1995

Student newspaper of California Polytechnic State University, San Luis Obispo, CA.https://digitalcommons.calpoly.edu/studentnewspaper/5879/thumbnail.jp

Type-2 Fuzzy Logic: Circumventing the Defuzzification Bottleneck

Type-2 fuzzy inferencing for generalised, discretised type-2 fuzzy sets has been impeded by the computational complexity of the defuzzification stage of the fuzzy inferencing system. Indeed this stage is so complex computationally that it has come to be known as the defuzzification bottleneck. The computational complexity derives from the enormous number of embedded sets that have to be individually processed in order to effect defuzzification. Two new approaches to type-2 defuzzification are presented, the sampling method and the Greenfield-Chiclana Collapsing Defuzzifier. The sampling method and its variant, elite sampling, are techniques for the defuzzification of generalised type-2 fuzzy sets. In these methods a relatively small sample of the totality of embedded sets is randomly selected and processed. The small sample size drastically reduces the computational complexity of the defuzzification process, so that it may be speedily accomplished. The Greenfield-Chiclana Collapsing Defuzzifier relies upon the concept of the representative embedded set, which is an embedded set having the same defuzzified value as the type-2 fuzzy set that is to be defuzzified. By a process termed collapsing the type-2 fuzzy set is converted into a type-1 fuzzy set which, as an approximation to the representative embedded set, is known as the representative embedded set approximation. This type-1 fuzzy set is easily defuzzified to give the defuzzified value of the original type-2 fuzzy set. By this method the computational complexity of type-2 defuzzification is reduced enormously, since the representative embedded set approximation replaces the entire collection of embedded sets. The strategy was conceived as a generalised method, but so far only the interval version has been derived mathematically. The grid method of discretisation for type-2 fuzzy sets is also introduced in this thesis. Work on the defuzzification of type-2 fuzzy sets began around the turn of the millennium. Since that time a number of investigators have contributed methods in this area. These different approaches are surveyed, and the major methods implemented in code prior to their experimental evaluation. In these comparative experiments the grid method of defuzzification is employed. The experimental results show beyond doubt that the collapsing method performs the best of the interval alternatives. However, though the sampling method performs well experimentally, the results do not demonstrate it to be the best performing generalised technique

\u3ci\u3eThe Symposium Proceedings of the 1998 Air Transport Research Group (ATRG), Volume 2\u3c/i\u3e

UNOAI Report 98-4https://digitalcommons.unomaha.edu/facultybooks/1153/thumbnail.jp

Decision support system for the environmental impact of e-business

With less than half a century's development, e-business and the Information and Communication Technologies it relies on, have been growing rapidly. With an even shorter history than the technology itself, the study of its impact on the environment and sustainable development in general, is still in its infancy. A review of past literature has revealed that the problem is complex. Both negative and positive impacts have been identified. Traditional systematic approaches have been found to be insufficient for this research topic. To explore the relationship further, a new methodology is proposed in this thesis. In particular the main objective of this PhD study is to demonstrate and develop an Expert Decision Support System at the meso level, to simulate the relationship between e-business and the environment. In pursuit of this aim, results are presented of two surveys that were conducted to collect data and build a knowledge base. Analysis of the data using various techniques was considered, based on data mining technologies and Fuzzy Logic. The development of the Expert Decision Support System is then discussed, adopting a two-way simulation approach. The forward chain of the system is developed based on Decision Support System technology, with the heart of the system built on Neural Networks. Calculation, estimation and prediction of environmental indicator values based e-business indicators are conducted in this part. The backward chain is based on Expert System technology, where conditions and rules are presented to reach certain pre-defined environmental targets. An individual company should then be able to use this system within a certain industry, for example, to simulate its environmental performance by adopting or limiting Information and Communication technologies. A demonstration of how the system can be used and operated on various occasions for different purposes is presented, based on four application scenarios: predictions, simulations, comparisons and solutions. It is claimed that the results from the Expert Decision Support System, which ideally should be integrated into a company's financial system and other information management systems, will provide important information that could be incorporated into a company's strategic plans, action plans and technological reformation. The research presents a pilot study which tries to not only build a quantitative model but also to construct a decision support system to simulate this relationship in the real world. It is claimed that the work both extends research methodologies in this field and endows traditional Neural Network applications with new meanings and challenges.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Decision support system for the environmental impact of e-business

With less than half a century's development, e-business and the Information and Communication Technologies it relies on, have been growing rapidly. With an even shorter history than the technology itself, the study of its impact on the environment and sustainable development in general, is still in its infancy. A review of past literature has revealed that the problem is complex. Both negative and positive impacts have been identified. Traditional systematic approaches have been found to be insufficient for this research topic. To explore the relationship further, a new methodology is proposed in this thesis. In particular the main objective of this PhD study is to demonstrate and develop an Expert Decision Support System at the meso level, to simulate the relationship between e-business and the environment. In pursuit of this aim, results are presented of two surveys that were conducted to collect data and build a knowledge base. Analysis of the data using various techniques was considered, based on data mining technologies and Fuzzy Logic. The development of the Expert Decision Support System is then discussed, adopting a two-way simulation approach. The forward chain of the system is developed based on Decision Support System technology, with the heart of the system built on Neural Networks. Calculation, estimation and prediction of environmental indicator values based e-business indicators are conducted in this part. The backward chain is based on Expert System technology, where conditions and rules are presented to reach certain pre-defined environmental targets. An individual company should then be able to use this system within a certain industry, for example, to simulate its environmental performance by adopting or limiting Information and Communication technologies. A demonstration of how the system can be used and operated on various occasions for different purposes is presented, based on four application scenarios: predictions, simulations, comparisons and solutions. It is claimed that the results from the Expert Decision Support System, which ideally should be integrated into a company's financial system and other information management systems, will provide important information that could be incorporated into a company's strategic plans, action plans and technological reformation. The research presents a pilot study which tries to not only build a quantitative model but also to construct a decision support system to simulate this relationship in the real world. It is claimed that the work both extends research methodologies in this field and endows traditional Neural Network applications with new meanings and challenges