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Synopsis
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.
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About the Author
DOAA ELSAYED MOHAMED AHMED B.Sc. Power & Electrical Machines Engineering, Faculty ofEngineering- Helwan, Helwan University Researcher assistant, Astronomy Department National Research Institute of Astronomy and Geophysics (NRIAG)
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- PublisherNoor Publishing
- Publication date2017
- ISBN 10 3330972262
- ISBN 13 9783330972261
- BindingPaperback
- LanguageEnglish
- Number of pages196
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Genetic Algorithms for optimizing FLC of Astronomical Telescope
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Noor Publishing Aug 2017, 2017
ISBN 10: 3330972262
ISBN 13: 9783330972261
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Taschenbuch. Condition: 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. Seller Inventory # 9783330972261
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Genetic Algorithms for optimizing FLC of Astronomical Telescope
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Taschenbuch. Condition: 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. Seller Inventory # 9783330972261
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