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Synopsis
1. 1 Introduction This book is written in two major parts. The ?rst part includes the int- ductory chapters consisting of Chapters 1 through 6. In part two, Chapters 7-26, we present the applications. This book continues our research into simulating fuzzy systems. We started with investigating simulating discrete event fuzzy systems ([7],[13],[14]). These systems can usually be described as queuing networks. Items (transactions) arrive at various points in the s- tem and go into a queue waiting for service. The service stations, preceded by a queue, are connected forming a network of queues and service, until the transaction ?nally exits the system. Examples considered included - chine shops, emergency rooms, project networks, bus routes, etc. Analysis of all of these systems depends on parameters like arrival rates and service rates. These parameters are usually estimated from historical data. These estimators are generally point estimators. The point estimators are put into the model to compute system descriptors like mean time an item spends in the system, or the expected number of transactions leaving the system per unit time. We argued that these point estimators contain uncertainty not shown in the calculations. Our estimators of these parameters become fuzzy numbers, constructed by placing a set of con?dence intervals one on top of another. Using fuzzy number parameters in the model makes it into a fuzzy system. The system descriptors we want (time in system, number leaving per unit time) will be fuzzy numbers.
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Simulating Continuous Fuzzy Systems (Studies in Fuzziness and Soft Computing, 188)
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Simulating Continuous Fuzzy Systems
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Studies continuous dynamical systems using crisp continuous simulationVariety of applications of fuzzy dynamical systems ranging from Bungee jumping to the AIDS epidemic to dynamical models in economicsCompanion text to Simula. N° de réf. du vendeur 5045767
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Simulating Continuous Fuzzy Systems
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Springer Berlin Heidelberg, Springer Berlin Heidelberg, 2010
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ISBN 13 : 9783642066689
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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - 1. 1 Introduction This book is written in two major parts. The rst part includes the int- ductory chapters consisting of Chapters 1 through 6. In part two, Chapters 7-26, we present the applications. This book continues our research into simulating fuzzy systems. We started with investigating simulating discrete event fuzzy systems ([7],[13],[14]). These systems can usually be described as queuing networks. Items (transactions) arrive at various points in the s- tem and go into a queue waiting for service. The service stations, preceded by a queue, are connected forming a network of queues and service, until the transaction nally exits the system. Examples considered included - chine shops, emergency rooms, project networks, bus routes, etc. Analysis of all of these systems depends on parameters like arrival rates and service rates. These parameters are usually estimated from historical data. These estimators are generally point estimators. The point estimators are put into the model to compute system descriptors like mean time an item spends in the system, or the expected number of transactions leaving the system per unit time. We argued that these point estimators contain uncertainty not shown in the calculations. Our estimators of these parameters become fuzzy numbers, constructed by placing a set of con dence intervals one on top of another. Using fuzzy number parameters in the model makes it into a fuzzy system. The system descriptors we want (time in system, number leaving per unit time) will be fuzzy numbers. N° de réf. du vendeur 9783642066689
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Simulating Continuous Fuzzy Systems
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ISBN 10 : 3642066682
ISBN 13 : 9783642066689
Neuf
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -1. 1 Introduction This book is written in two major parts. The rst part includes the int- ductory chapters consisting of Chapters 1 through 6. In part two, Chapters 7-26, we present the applications. This book continues our research into simulating fuzzy systems. We started with investigating simulating discrete event fuzzy systems ([7],[13],[14]). These systems can usually be described as queuing networks. Items (transactions) arrive at various points in the s- tem and go into a queue waiting for service. The service stations, preceded by a queue, are connected forming a network of queues and service, until the transaction nally exits the system. Examples considered included - chine shops, emergency rooms, project networks, bus routes, etc. Analysis of all of these systems depends on parameters like arrival rates and service rates. These parameters are usually estimated from historical data. These estimators are generally point estimators. The point estimators are put into the model to compute system descriptors like mean time an item spends in the system, or the expected number of transactions leaving the system per unit time. We argued that these point estimators contain uncertainty not shown in the calculations. Our estimators of these parameters become fuzzy numbers, constructed by placing a set of con dence intervals one on top of another. Using fuzzy number parameters in the model makes it into a fuzzy system. The system descriptors we want (time in system, number leaving per unit time) will be fuzzy numbers. 216 pp. Englisch. N° de réf. du vendeur 9783642066689
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Simulating Continuous Fuzzy Systems
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Simulating Continuous Fuzzy Systems
Edité par
Springer Berlin Heidelberg, Springer Berlin Heidelberg Feb 2010, 2010
ISBN 10 : 3642066682
ISBN 13 : 9783642066689
Neuf
Taschenbuch
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
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Taschenbuch. Etat : Neu. Neuware -1. 1 Introduction This book is written in two major parts. The rst part includes the int- ductory chapters consisting of Chapters 1 through 6. In part two, Chapters 7-26, we present the applications. This book continues our research into simulating fuzzy systems. We started with investigating simulating discrete event fuzzy systems ([7],[13],[14]). These systems can usually be described as queuing networks. Items (transactions) arrive at various points in the s- tem and go into a queue waiting for service. The service stations, preceded by a queue, are connected forming a network of queues and service, until the transaction nally exits the system. Examples considered included - chine shops, emergency rooms, project networks, bus routes, etc. Analysis of all of these systems depends on parameters like arrival rates and service rates. These parameters are usually estimated from historical data. These estimators are generally point estimators. The point estimators are put into the model to compute system descriptors like mean time an item spends in the system, or the expected number of transactions leaving the system per unit time. We argued that these point estimators contain uncertainty not shown in the calculations. Our estimators of these parameters become fuzzy numbers, constructed by placing a set of con dence intervals one on top of another. Using fuzzy number parameters in the model makes it into a fuzzy system. The system descriptors we want (time in system, number leaving per unit time) will be fuzzy numbers.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 216 pp. Englisch. N° de réf. du vendeur 9783642066689
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Simulating Continuous Fuzzy Systems
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Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, 2010
ISBN 10 : 3642066682
ISBN 13 : 9783642066689
Neuf
Couverture souple
Edition originale
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Etat : New. Series: Studies in Fuzziness and Soft Computing. Num Pages: 202 pages, 22 black & white tables, biography. BIC Classification: GPFC; UGK. Category: (P) Professional & Vocational. Dimension: 234 x 156 x 11. Weight in Grams: 338. . 2010. 1st ed. Softcover of orig. ed. 2006. Paperback. . . . . N° de réf. du vendeur V9783642066689
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Simulating Continuous Fuzzy Systems
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ISBN 10 : 3642066682
ISBN 13 : 9783642066689
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Simulating Continuous Fuzzy Systems
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Simulating Continuous Fuzzy Systems (Studies in Fuzziness and Soft Computing, 188)
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