Linguistic Fuzzy Logic Methods In Social Sciences

Name: Medien! In A Personal Note He States: âWhen I Wrote My L965 Paper, I Expected That Fuzzy Set Theory Would Be Applied Primarily In The Realm Of Human Sciences.
Brand: Springer Nature
SKU: CBAC-42584
Price: 109.99 EUR
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About The In a sixteen-page article, modestly titled âFuzzy Setsâ and published in the journal Information and Control, Zadeh launched a multi-disciplinary revolution.â In fact, the first comprehensive examination of fuzzy sets by a social scientist did not appear until 1987, a full twenty-two years after the publication of Zadehâs seminal article, when Michael Smithson, an Australian psychologist, published Fuzzy Set Analysis for Behavioral and Social Sciences. The start was relatively slow, but momentum gathered quickly

The modern origin of fuzzy sets, fuzzy algebra, fuzzy decision making, and âcomputing with wordsâ is conventionally traced to Lotfi Zadehâs publication in 1965 of his path-breaking refutation of binary set theory. Zadeh was surprised by this development. Contrary to my expectation, fuzzy set theory and fuzzy logic are applied in the main in physical and engineering sciences.â In fact, the first comprehensive examination of fuzzy sets by a social scientist did not appear until 1987, a full twenty-two years after the publication of Zadehâs seminal article, when Michael Smithson, an Australian psychologist, published Fuzzy Set Analysis for Behavioral and Social Sciences. Almost all applications of Zadehâs ideas have been in highly technical scientific fields, not in the social sciences. At present, citations to Zadehâs publications are running at a rate of about 1,500-2,000 per year, and this rate continues to rise. From 1970 to 1979 there were about 500 journal publications with the word fuzzy in the title; from 2000 to 2009 there were more than 35,000. In a personal note he states: âWhen I wrote my l965 paper, I expected that fuzzy set theory would be applied primarily in the realm of human sciences. The start was relatively slow, but momentum gathered quickly. In a sixteen-page article, modestly titled âFuzzy Setsâ and published in the journal Information and Control, Zadeh launched a multi-disciplinary revolution.

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This book presents a novel approach to the advanced and sophisticated case, called intelligent counting, in which the objects of counting are imprecisely, fuzzily specified.

The monograph exposes the foundations of a new decision theory with imperfect decision-relevant information on environment and a decision makerâs behavior.

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Linguistic Fuzzy Logic Methods In Social Sciences

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Applications are to queuing theory, Markov chains, inventory control, decision theory and reliability theory.

Fuzzy Probabilities A fuzzy normal random variable has the normal distribution with fuzzy number mean and variance. Instead of using a point estimate calculated from the data we propose using fuzzy numbers which are constructed from a set of confidence intervals.In probability and statistics we often have to estimate probabilities and parameters in probability distributions using a random sample.

Researchers, practitioners and students in management science, operations research, information science, system science and engineering science will find this work a useful reference.

How do we model the multiple objective decision making problems under fuzzy-like environments? How do you deal with these models? What are the fuzzy-like environments? Fuzzy-Like Multiple Objective Decision Making In order to answer these questions, this book provides an up-to-date methodology system for fuzzy-like multiple objective decision making, which includes modelling system, model analysis system, algorithm system and application system in structure optimization problem, selection problem, purchasing problem, inventory problem, logistics problem and so on.

A large spectrum of problems that may be encountered during decision making and decision analysis in the areas of economics and the social sciences, together with a broad range of tools and techniques that may be used to solve those problems, are presented in detail in this book, making it an ideal reference work for all those interested in analyzing and implementing mathematical tools for application to relevant issues involving the economy and society.

Decisions in these contexts have to meet precise coherence standards and achieve a significant degree of sharing, consensus and acceptance, even in uncertain and fuzzy environments.

The present book outlines a new approach to possibilistic clustering in which the sought clustering structure of the set of objects is based directly on the formal definition of fuzzy cluster and the possibilistic memberships are determined directly from the values of the pairwise similarity of objects.

Here, some techniques that might be useful at this purpose are outlined, including a methodology for constructing a set of labeled objects for a semi-supervised clustering algorithm, a methodology for reducing analyzed attribute space dimensionality and a methods for asymmetric data processing.

The present book outlines a new approach to possibilistic clustering in which the sought clustering structure of the set of objects is based directly on the formal definition of fuzzy cluster and the possibilistic memberships are determined directly from the values of the pairwise similarity of objects.

. Here, some techniques that might be useful at this purpose are outlined, including a methodology for constructing a set of labeled objects for a semi-supervised clustering algorithm, a methodology for reducing analyzed attribute space dimensionality and a methods for asymmetric data processing. This book addresses engineers, scientists, professors, students and post-graduate students, who are interested in and work with fuzzy clustering and its applications Â Â The proposed approach can be used for solving different classification problems.