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Añadir al carritoTaschenbuch. Condición: Neu. Ultrasonic Fluid Quantity Measurement in Dynamic Vehicular Applications | A Support Vector Machine Approach | Jenny Terzic (u. a.) | Taschenbuch | xiv | Englisch | 2015 | Springer | EAN 9783319033273 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Idioma: Inglés
Publicado por Springer International Publishing, Springer International Publishing, 2015
ISBN 10: 3319033271 ISBN 13: 9783319033273
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Añadir al carritoTaschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Accurate fluid level measurement in dynamic environments can be assessed using a Support Vector Machine (SVM) approach. SVM is a supervised learning model that analyzes and recognizes patterns. It is a signal classification technique which has far greater accuracy than conventional signal averaging methods.Ultrasonic Fluid Quantity Measurement in Dynamic Vehicular Applications: A Support Vector Machine Approach describes the research and development of a fluid level measurement system for dynamic environments. The measurement system is based on a single ultrasonic sensor. A Support Vector Machines (SVM) based signal characterization and processing system has been developed to compensate for the effects of slosh and temperature variation in fluid level measurement systems used in dynamic environments including automotive applications. It has been demonstrated that a simple ni-SVM model with Radial Basis Function (RBF) Kernel with the inclusion of a Moving Median filter could be used to achieve the high levels of accuracy required for fluid level measurement in dynamic environments.Aimed toward graduate and postgraduate students, researchers, and engineers studying applications of artificial intelligence, readers will learn about a measurement system that is based on a single ultrasonic sensor which can achieve the high levels of accuracy required for fluid level measurement in dynamic environments.
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Publicado por Springer International Publishing Jul 2015, 2015
ISBN 10: 3319033271 ISBN 13: 9783319033273
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Accurate fluid level measurement in dynamic environments can be assessed using a Support Vector Machine (SVM) approach. SVM is a supervised learning model that analyzes and recognizes patterns. It is a signal classification technique which has far greater accuracy than conventional signal averaging methods.Ultrasonic Fluid Quantity Measurement in Dynamic Vehicular Applications: A Support Vector Machine Approach describes the research and development of a fluid level measurement system for dynamic environments. The measurement system is based on a single ultrasonic sensor. A Support Vector Machines (SVM) based signal characterization and processing system has been developed to compensate for the effects of slosh and temperature variation in fluid level measurement systems used in dynamic environments including automotive applications. It has been demonstrated that a simple ni-SVM model with Radial Basis Function (RBF) Kernel with the inclusion of a Moving Median filter could be used to achieve the high levels of accuracy required for fluid level measurement in dynamic environments.Aimed toward graduate and postgraduate students, researchers, and engineers studying applications of artificial intelligence, readers will learn about a measurement system that is based on a single ultrasonic sensor which can achieve the high levels of accuracy required for fluid level measurement in dynamic environments. 144 pp. Englisch.
Idioma: Inglés
Publicado por Springer International Publishing, 2015
ISBN 10: 3319033271 ISBN 13: 9783319033273
Librería: moluna, Greven, Alemania
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Añadir al carritoKartoniert / Broschiert. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Covers the dynamic aspect (sloshing) of the fluid level measurement system in the vehicle and uses SVM as a method to improve accuracy of the system and recognize the sloshing pattern in the fuel tank with superior accuracy Discusses extensive exper.
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Añadir al carritoCondición: New. Print on Demand pp. 129.
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Añadir al carritoCondición: New. PRINT ON DEMAND pp. 129.
Idioma: Inglés
Publicado por Springer, Springer Jul 2015, 2015
ISBN 10: 3319033271 ISBN 13: 9783319033273
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Accurate fluid level measurement in dynamic environments can be assessed using a Support Vector Machine (SVM) approach. SVM is a supervised learning model that analyzes and recognizes patterns. It is a signal classification technique which has far greater accuracy than conventional signal averaging methods.Ultrasonic Fluid Quantity Measurement in Dynamic Vehicular Applications: A Support Vector Machine Approach describes the research and development of a fluid level measurement system for dynamic environments. The measurement system is based on a single ultrasonic sensor. A Support Vector Machines (SVM) based signal characterization and processing system has been developed to compensate for the effects of slosh and temperature variation in fluid level measurement systems used in dynamic environments including automotive applications. It has been demonstrated that a simple ¿-SVM model with Radial Basis Function (RBF) Kernel with the inclusion of a Moving Median filter could be used to achieve the high levels of accuracy required for fluid level measurement in dynamic environments.Aimed toward graduate and postgraduate students, researchers, and engineers studying applications of artificial intelligence, readers will learn about a measurement system that is based on a single ultrasonic sensor which can achieve the high levels of accuracy required for fluid level measurement in dynamic environments.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 144 pp. Englisch.