Fuzzy sets are sets whose elements have degrees of membership. Fuzzy set theory was formalized by Professor Lotfi Zadeh at the University of California in 1965 as an extension of the classical notion of set. In classical set theory, the membership of elements in a set is assessed in binary terms according to a bivalent condition an element either belongs or does not belong to the set. Fuzzy sets generalize classical sets are special cases of the membership functions of fuzzy sets, if the latter only take values 0 or 1. Classical bivalent sets are in fuzzy set theory usually called crisp sets. On the other hand fuzzy set is more specified than crisp set. It can take a decision between membership grade 0 to 1, i.e. unit interval [0, 1]. This book attempts to fill the needs of the algorithms of Newton’s method, Fixed-Point Iteration method and Bisection method which are used to solve fuzzy non-linear equations for the linear fuzzy real number. The procedures to obtain solutions of different types of fuzzy linear equations have also been discussed. The book has been outlined into four chapters.
"synopsis" may belong to another edition of this title.
Goutam Kumar Saha has obtained M.S. degree from the Department of Mathematics, University of Dhaka, Bangladesh and now he is a Lecturer of Department of Mathematics, BUBT. Shapla Shirin is an Associate Professor of Department of Mathematics, University of Dhaka, Bangladesh. Their main topic of interest is Fuzzy Set Theory and its applications.
"About this title" may belong to another edition of this title.
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Fuzzy sets are sets whose elements have degrees of membership. Fuzzy set theory was formalized by Professor Lotfi Zadeh at the University of California in 1965 as an extension of the classical notion of set. In classical set theory, the membership of elements in a set is assessed in binary terms according to a bivalent condition an element either belongs or does not belong to the set. Fuzzy sets generalize classical sets are special cases of the membership functions of fuzzy sets, if the latter only take values 0 or 1. Classical bivalent sets are in fuzzy set theory usually called crisp sets. On the other hand fuzzy set is more specified than crisp set. It can take a decision between membership grade 0 to 1, i.e. unit interval [0, 1]. This book attempts to fill the needs of the algorithms of Newton s method, Fixed-Point Iteration method and Bisection method which are used to solve fuzzy non-linear equations for the linear fuzzy real number. The procedures to obtain solutions of different types of fuzzy linear equations have also been discussed. The book has been outlined into four chapters. 84 pp. Englisch. Seller Inventory # 9783847316671
Seller: moluna, Greven, Germany
Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Saha Goutam KumarGoutam Kumar Saha has obtained M.S. degree from the Department of Mathematics, University of Dhaka, Bangladesh and now he is a Lecturer of Department of Mathematics, BUBT. Shapla Shirin is an Associate Professor of . Seller Inventory # 5509582
Quantity: Over 20 available
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Fuzzy sets are sets whose elements have degrees of membership. Fuzzy set theory was formalized by Professor Lotfi Zadeh at the University of California in 1965 as an extension of the classical notion of set. In classical set theory, the membership of elements in a set is assessed in binary terms according to a bivalent condition an element either belongs or does not belong to the set. Fuzzy sets generalize classical sets are special cases of the membership functions of fuzzy sets, if the latter only take values 0 or 1. Classical bivalent sets are in fuzzy set theory usually called crisp sets. On the other hand fuzzy set is more specified than crisp set. It can take a decision between membership grade 0 to 1, i.e. unit interval [0, 1]. This book attempts to fill the needs of the algorithms of Newton's method, Fixed-Point Iteration method and Bisection method which are used to solve fuzzy non-linear equations for the linear fuzzy real number. The procedures to obtain solutions of different types of fuzzy linear equations have also been discussed. The book has been outlined into four chapters.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 84 pp. Englisch. Seller Inventory # 9783847316671
Seller: AHA-BUCH GmbH, Einbeck, Germany
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Fuzzy sets are sets whose elements have degrees of membership. Fuzzy set theory was formalized by Professor Lotfi Zadeh at the University of California in 1965 as an extension of the classical notion of set. In classical set theory, the membership of elements in a set is assessed in binary terms according to a bivalent condition an element either belongs or does not belong to the set. Fuzzy sets generalize classical sets are special cases of the membership functions of fuzzy sets, if the latter only take values 0 or 1. Classical bivalent sets are in fuzzy set theory usually called crisp sets. On the other hand fuzzy set is more specified than crisp set. It can take a decision between membership grade 0 to 1, i.e. unit interval [0, 1]. This book attempts to fill the needs of the algorithms of Newton s method, Fixed-Point Iteration method and Bisection method which are used to solve fuzzy non-linear equations for the linear fuzzy real number. The procedures to obtain solutions of different types of fuzzy linear equations have also been discussed. The book has been outlined into four chapters. Seller Inventory # 9783847316671
Seller: preigu, Osnabrück, Germany
Taschenbuch. Condition: Neu. Solution of Fuzzy Linear and Non-linear Equations | Concepts of Negative Fuzzy Numbers Using In Linear Fuzzy Equations | Goutam Kumar Saha (u. a.) | Taschenbuch | 84 S. | Englisch | 2012 | LAP LAMBERT Academic Publishing | EAN 9783847316671 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Seller Inventory # 106419661
Seller: Mispah books, Redhill, SURRE, United Kingdom
Paperback. Condition: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book. Seller Inventory # ERICA79638473166726
Quantity: 1 available