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Taschenbuch. Etat : Neu. Genetic Algorithms for optimizing FLC of Astronomical Telescope | Doaa Eid (u. a.) | Taschenbuch | 196 S. | Englisch | 2017 | Noor Publishing | EAN 9783330972261 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.

Paperback. Etat : Brand New. 196 pages. 8.66x5.91x0.45 inches. In Stock.

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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book is concerned with the development and implementation of optimizing fuzzy logic controller for a telescope system. The knowledge base of a fuzzy logic controller (FLC) encloses expert knowledge and consists of the data base (membership functions) and Rule-Base of the controller. Optimization of membership function is critical to performance of the controller and has traditionally been achieved through a process of trial and error. Genetic Algorithms (GA's) provide such a method. They are numerical search methods which use operators consistent with evolutionary theory and find application in many disciplines,particularly function optimization problems.Although not learning algorithms in the strictest sense. GA's can be applied to learning tasks. Today, it is more common to test controllers using simulated models in a real-time environment. This methodology offers several distinct advantages a simulation can help reduce development cycles, cut overall cost, prevent costly failures, increase repeatability through controlled environment and test a subsystem exhaustively before integrating into the system. 196 pp. Englisch.

Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book is concerned with the development and implementation of optimizing fuzzy logic controller for a telescope system. The knowledge base of a fuzzy logic controller (FLC) encloses expert knowledge and consists of the data base (membership functions) and Rule-Base of the controller. Optimization of membership function is critical to performance of the controller and has traditionally been achieved through a process of trial and error. Genetic Algorithms (GA's) provide such a method. They are numerical search methods which use operators consistent with evolutionary theory and find application in many disciplines,particularly function optimization problems.Although not learning algorithms in the strictest sense. GA's can be applied to learning tasks. Today, it is more common to test controllers using simulated models in a real-time environment. This methodology offers several distinct advantages a simulation can help reduce development cycles, cut overall cost, prevent costly failures, increase repeatability through controlled environment and test a subsystem exhaustively before integrating into the system.Books on Demand GmbH, Überseering 33, 22297 Hamburg 196 pp. Englisch.

Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book is concerned with the development and implementation of optimizing fuzzy logic controller for a telescope system. The knowledge base of a fuzzy logic controller (FLC) encloses expert knowledge and consists of the data base (membership functions) and Rule-Base of the controller. Optimization of membership function is critical to performance of the controller and has traditionally been achieved through a process of trial and error. Genetic Algorithms (GA's) provide such a method. They are numerical search methods which use operators consistent with evolutionary theory and find application in many disciplines,particularly function optimization problems.Although not learning algorithms in the strictest sense. GA's can be applied to learning tasks. Today, it is more common to test controllers using simulated models in a real-time environment. This methodology offers several distinct advantages a simulation can help reduce development cycles, cut overall cost, prevent costly failures, increase repeatability through controlled environment and test a subsystem exhaustively before integrating into the system.