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Friday, May 8, 2020 | History

4 edition of Applications of fuzzy sets and the theory of evidence to accounting, II found in the catalog.

Applications of fuzzy sets and the theory of evidence to accounting, II

  • 246 Want to read
  • 1 Currently reading

Published by JAI Press in Stamford, Conn .
Written in English

    Subjects:
  • Accounting -- Decision making.,
  • Fuzzy sets.,
  • Managerial accounting.

  • Edition Notes

    Includes bibliographical references.

    Statementedited by Philip H. Seigel ; co-edited by Kursheed Omer, Andre de Korvin, Awni Zebda.
    SeriesStudies in managerial and financial accounting ;, v. 7
    ContributionsSiegel, Philip H.
    Classifications
    LC ClassificationsHF5657 .A662 1998
    The Physical Object
    Paginationxvii, 310 p. ;
    Number of Pages310
    ID Numbers
    Open LibraryOL477478M
    ISBN 100762304170
    LC Control Number98203284

    Aims & Scope of the Journal. Since its launching in , the journal Fuzzy Sets and Systems has been devoted to the international advancement of the theory and application of fuzzy sets and theory of fuzzy sets now encompasses a well organized corpus of basic notions including (and not restricted to) aggregation operations, a generalized theory of relations, specific measures of. Coverage of theoretical fuzzy concepts is quite complete, including theory of fuzzy sets, fuzzy arithmetic, fuzzy relations, possiblity theory, fuzzy logic and uncertainty-based information. The applications section presents theory which could be useful in applications rather than the applications /5(7).

    Purchase Fuzzy Theory Systems - 1st Edition. Print Book & E-Book. ISBN , Defuzzification to Crisp Sets λ-Cuts for Fuzzy Relations Defuzzification to Scalars Summary References Problems 5 Logic and Fuzzy Systems Part I: Logic Classical Logic Fuzzy Logic Part II: Fuzzy Systems Summary References Problems 6 Historical Methods of Developing Membership.

    Privacy and Cookies. We use cookies to give you the best experience on our website. By continuing, you're agreeing to use of cookies. We have recently updated our policy. A fuzzy concept is a concept of which the boundaries of application can vary considerably according to context or conditions, instead of being fixed once and for all. This means the concept is vague in some way, lacking a fixed, precise meaning, without however being unclear or meaningless altogether. It has a definite meaning, which can be made more precise only through further elaboration.


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Applications of fuzzy sets and the theory of evidence to accounting, II Download PDF EPUB FB2

An analysis of fuzzy sets and the theory of evidence to accounting. It is divided into parts, covering: methodology; inference; prediction; and neural networks.

Amazon Giveaway allows you to run promotional giveaways in order to create buzz, reward your audience, and attract new followers and customers. This item: Studies in Managerial and Financial Accounting, Volume 7: Applications of Fuzzy Sets and the Theory of Evidence to Accounting II (v.

Dealing with ambiguity in the tax law - an application of rough set theory to the determination of debt worthlessness, J.M. Hagan et al; ambiguity and vagueness in determining reasonable compensation for closely held corporations - the use of rough and fuzzy set theory to develop decision rules, J.M.

Hagan et al; going concern audit decision outcomes - a fuzzy set approach, J. Spiceland et al; an. fuzzy sets and many examples have been supplied to understand the concept of fuzzy sets. Furthermore, in the years andZadeh, explain the Applications of fuzzy sets and the theory of evidence to accounting of fuzzy sets that result from the extension as well as a fuzzy logic based on the set theory.

After that, Zimmermann ) introduced recent application of fuzzy set theoryCited by: 1. Fuzzy Set Theory - And Its Applications, Third Edition is a textbook for courses in fuzzy set theory.

It can also be used as an introduction to the : Hans-Jürgen Zimmermann. Part II: Applications of Fuzzy Set Theory 9 Fuzzy Logic and Approximate Reasoning Linguistic Variables Fuzzy Logic Classical Logics Revisited Linguistic Truth Tables Approximate and Plausible Reasoning Fuzzy Languages Support Logic Programming and Fril Introduction Fril Rules Job assignment is one of most important functions in human resource management.

It presents a new model which optimizes the multi-objectives allocation problem by using fuzzy logic strategic. The fuzzy experience evaluation matrix indicates the score of certain employee on certain : Zhen Xu, Binheng Song, Liang Chen.

The book presents the basic rudiments of fuzzy set theory and fuzzy logic and their applications in a simple and easy to understand manner. It is written with a general type of reader in mind.

The book avoids the extremes of abstract mathematical proofs as well as specialized technical details of different areas of : Chander Mohan. After probability theory, fuzzy set theory and evidence theory, rough set theory is a new mathematical tool for dealing with vague, imprecise, inconsistent and uncertain knowledge.

In recent years, the research and applications on rough set theory have attracted more and more researchers' by: Ijiri Y. (), “The theory of accounting measurement, Studies” in Accounting Research, 10, American Accounting Association. Google Scholar Korvin A. (), “Uncertainty methods in accounting: a methodological overview”, in Seigel P.H., de Korvin A., Omer K.

(eds), Applications of fuzzy sets and the theory of evidence to accounting, Cited by: 6. Since its inception, the theory of fuzzy sets has advanced in a variety of ways and in many disciplines.

Applications of fuzzy technology can be found in artificial intelligence, computer science, control engineering, decision theory, expert systems, logic, management science, operations research, robotics, and others. Theoretical advances have been made in many directions/5(4).

A Category-Theoretical Approach to Fuzzy Sets Gabriella Pigozzi, King’s College London This thesis analyzes the notion of a fuzzy set using a category-theoretical approach.

A fuzzy set is a set whose elements belong to the set only with a certain degree represented by a real number in the interval [0,1]. The manipulation of fuzzy sets is. Accounting and Auditing Department Analytical Study On The Reflections Of Integration Between The Philosophy Of Fuzzy Logic And The Quality Of Accounting Information On The Investment Decision Makers (Field Study) Thesis Prepared By: Mohamed Lotfy Abd El Raouf Abo El Azm Accountant at Suez Canal Authority To obtain a master's degree in accounting.

notions that have been introduced in the framework of fuzzy set theory. Chapter 1 provides the basic definitions of various kinds of fuzzy sets, set-theoretic operations, and properties. Lastly, measures of fuzziness are described. Chapter 2 introduces a very general principle of fuzzy set theory: the so-called extension Size: 9MB.

details the advances that have taken place in fuzzy set theory and fuzzy logic in recent years. requires only a basic knowledge of classical (nonfuzzy) set theory, classical (two-valued) logic, and probability theory. includes all bibliographical, historical, and other side remarks in the notes that follow each individual bility: Available.

Properties of α-cuts II Theorem (Representation Theorem) Let µ ∈ F(X).Then µ(x) = sup α∈[0,1] n min(α,χ[µ]α (x))o where χ [µ]α (x) =1, if x ∈ [µ]α 0, otherwise.

So, fuzzy set can be obtained as upper envelope of its α-cuts. Simply draw α-cuts parallel to horizontal axis in height of α. In applications it is recommended to select finite subset L ⊆ [0,1] ofFile Size: 1MB.

The primary purpose of this book is to provide the reader with a comprehensive coverage of theoretical foundations of fuzzy set theory and fuzzy logic, as well as a broad overview of the increasingly important applications of these novel areas of mathematics. Although it is written as a text for a course at the graduate or upper division undergraduate level, the book is also suitable for self 5/5(1).

M.K. Luhandjula: Fuzzy Mathematical Programming: Theory, Application and Extension † A fuzzy number is a normal and convex fuzzy set of R. A fuzzy number is well suited for representing vague data [11].

For instance the vague datum: \close to flve" can be represented by the fuzzy number „ as in Fig 1. It is the premise of this book that this perceived tension between probability theory and fuzzy set theory is precisely the mechanism necessary for scientific advancement.

Within this tension are the searches, trials and errors, and shortcomings that all play a part in the evolution of any theory and its applications. Articles written on the occasion of the 50th anniversary of fuzzy set theory Didier Dubois Henri Prade (with Davide Ciucci & Jim Bezdek) Summary: The first paper by Lotfi A.

Zadeh on fuzzy sets appeared 50 years ago. On the occasion of this anniversary, the authors of this report have been led to contribute a series of papers in relation.

These averaging operations on fuzzy sets have no counterparts in classical set theory and, because of this, extensions of fuzzy sets into fuzzy logic allow for the latter to be much more expressive in natural categories revealed by empirical data or required by intuition (Belohlavek et al., ).Fuzzy Sets and Fuzzy Logic is a true magnum opus.

An enlargement of Fuzzy Sets, Uncertainty, and Information—an earlier work of Professor Klir and Tina Folger—Fuzzy Sets and Fuzzy Logic addresses practically every significant topic in the broad expanse of the union of fuzzy set theory and fuzzy logic.

To me Fuzzy Sets and Fuzzy Logic is a remarkable achievement; it covers its vast.ELSEVIER Fuzzy Sets and Systems 92 () FUZ2Y sets and systems Cost-benefit analysis, benefit accounting and fuzzy decisions. (I). Theory Kofi Kissi Dompere Department of Economics, Howard University, Washington, DCUSA Received December ; revised June Abstract In this essay, we present a logical framework for developing a comprehensive benefit information set Cited by: 4.