fuzzy evolutionary computation (18 Ergebnisse)

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Zustand: Good. Most items will be dispatched the same or the next working day. A copy that has been read but remains in clean condition. All of the pages are intact and the cover is intact and the spine may show signs of wear. The book may have minor markings which are not specifically mentioned.

Zustand: New. pp. 260 49:B&W 6.14 x 9.21 in or 234 x 156 mm (Royal 8vo) Perfect Bound on White w/Gloss Lam.

Zustand: New. pp. x + 307 Illus.

Hardcover. Zustand: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less.

Zustand: Good. Schutzumschlag angerissen. Cover leicht verschmutzt. Buchschnitt leicht verschmutzt.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book includes a selection of twelve carefully revised papers chosen from the papers accepted for presentation at the 4th IEEE/Nagoya-University World Wisepersons Workshop held in Nagoya in November 1995.The combining of the technologies of fuzzy logic, neural networks, and evolutionary computation is expected to open up a new paradigm of machine learning for the realization of human-like information generating systems. The excellent papers presented are organized in sections on fuzzy and evolutionary computation, fuzzy and learning automata, fuzzy and neural networks, genetic algorithms, and CAM-brain.

Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 260 | Sprache: Englisch | Produktart: Bücher | This book includes a selection of twelve carefully revised papers chosen from the papers accepted for presentation at the 4th IEEE/Nagoya-University World Wisepersons Workshop held in Nagoya in November 1995. The combining of the technologies of fuzzy logic, neural networks, and evolutionary computation is expected to open up a new paradigm of machine learning for the realization of human-like information generating systems. The excellent papers presented are organized in sections on fuzzy and evolutionary computation, fuzzy and learning automata, fuzzy and neural networks, genetic algorithms, and CAM-brain.

Zustand: New. pp. 312.

Hardcover. Zustand: Brand New. 1st edition. 378 pages. 10.00x7.00x1.00 inches. In Stock.

Zustand: New. Provides an in-depth and even treatment of the three pillars of computational intelligence and how they relate to one another This book covers the three fundamental topics that form the basis of computational intelligence: neural networks, fuzzy systems, and evolutionary computation. Series: IEEE Press Series on Computational Intelligence. Num Pages: 378 pages. BIC Classification: UYQ. Category: (P) Professional & Vocational. Dimension: 235 x 163 x 25. Weight in Grams: 658. . 2016. Hardback. . . . . Books ship from the US and Ireland.

Hardcover. Zustand: Brand New. 307 pages. 9.25x6.25x1.00 inches. In Stock.

Zustand: New. pp. 340 52:B&W 6.14 x 9.21in or 234 x 156mm (Royal 8vo) Case Laminate on White w/Gloss Lam.

Buch. Zustand: Neu. Neuware - Provides an in-depth and even treatment of the three pillars of computational intelligence and how they relate to one another.

Zustand: New. As of today, Evolutionary Computing and Fuzzy Set Computing are two mature, wen -developed, and higbly advanced technologies of information processing. Bach of them has its own clearly defined research agenda, specific goals to be achieved, and a wen setUed.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - As of today, Evolutionary Computing and Fuzzy Set Computing are two mature, wen -developed, and higbly advanced technologies of information processing. Bach of them has its own clearly defined research agenda, specific goals to be achieved, and a wen setUed algorithmic environment. Concisely speaking, Evolutionary Computing (EC) is aimed at a coherent population -oriented methodology of structural and parametric optimization of a diversity of systems. In addition to this broad spectrum of such optimization applications, this paradigm otTers an important ability to cope with realistic goals and design objectives reflected in the form of relevant fitness functions. The GA search (which is often regarded as a dominant domain among other techniques of EC such as evolutionary strategies, genetic programming or evolutionary programming) delivers a great deal of efficiency helping navigate through large search spaces. The main thrust of fuzzy sets is in representing and managing nonnumeric (linguistic) information. The key notion (whose conceptual as weH as algorithmic importance has started to increase in the recent years) is that of information granularity. It somewhat concurs with the principle of incompatibility coined by L. A. Zadeh. Fuzzy sets form a vehic1e helpful in expressing a granular character of information to be captured. Once quantified via fuzzy sets or fuzzy relations, the domain knowledge could be used efficiently very often reducing a heavy computation burden when analyzing and optimizing complex systems.

Encuadernación de tapa dura. Zustand: Aceptable. Editor Nikos Mastorakis. Danver. Edit. World Scientific and Engineering Society Press. 2001. 24x17 cm. 349 págs. Ilust. texto a dos columnas. Cartoné edit. Texto en inglés. # mecánica.

Buch. Zustand: Neu. Neuware - As of today, Evolutionary Computing and Fuzzy Set Computing are two mature, wen -developed, and higbly advanced technologies of information processing. Bach of them has its own clearly defined research agenda, specific goals to be achieved, and a wen setUed algorithmic environment. Concisely speaking, Evolutionary Computing (EC) is aimed at a coherent population -oriented methodology of structural and parametric optimization of a diversity of systems. In addition to this broad spectrum of such optimization applications, this paradigm otTers an important ability to cope with realistic goals and design objectives reflected in the form of relevant fitness functions. The GA search (which is often regarded as a dominant domain among other techniques of EC such as evolutionary strategies, genetic programming or evolutionary programming) delivers a great deal of efficiency helping navigate through large search spaces. The main thrust of fuzzy sets is in representing and managing nonnumeric (linguistic) information. The key notion (whose conceptual as weH as algorithmic importance has started to increase in the recent years) is that of information granularity. It somewhat concurs with the principle of incompatibility coined by L. A. Zadeh. Fuzzy sets form a vehic1e helpful in expressing a granular character of information to be captured. Once quantified via fuzzy sets or fuzzy relations, the domain knowledge could be used efficiently very often reducing a heavy computation burden when analyzing and optimizing complex systems.