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Computing Statistics under Interval and Fuzzy Uncertainty: Applications to Computer Science and Engineering: 393 (Studies in Computational Intelligence) - Tapa blanda
Sinopsis
In many practical situations, we are interested in statistics characterizing a population of objects: e.g. in the mean height of people from a certain area.
Most algorithms for estimating such statistics assume that the sample values are exact. In practice, sample values come from measurements, and measurements are never absolutely accurate. Sometimes, we know the exact probability distribution of the measurement inaccuracy, but often, we only know the upper bound on this inaccuracy. In this case, we have interval uncertainty: e.g. if the measured value is 1.0, and inaccuracy is bounded by 0.1, then the actual (unknown) value of the quantity can be anywhere between 1.0 - 0.1 = 0.9 and 1.0 + 0.1 = 1.1. In other cases, the values are expert estimates, and we only have fuzzy information about the estimation inaccuracy.
This book shows how to compute statistics under such interval and fuzzy uncertainty. The resulting methods are applied to computer science (optimal scheduling of different processors), to information technology (maintaining privacy), to computer engineering (design of computer chips), and to data processing in geosciences, radar imaging, and structural mechanics.
"Sinopsis" puede pertenecer a otra edición de este libro.
De la contraportada
In many practical situations, we are interested in statistics characterizing a population of objects: e.g. in the mean height of people from a certain area.
Most algorithms for estimating such statistics assume that the sample values are exact. In practice, sample values come from measurements, and measurements are never absolutely accurate. Sometimes, we know the exact probability distribution of the measurement inaccuracy, but often, we only know the upper bound on this inaccuracy. In this case, we have interval uncertainty: e.g. if the measured value is 1.0, and inaccuracy is bounded by 0.1, then the actual (unknown) value of the quantity can be anywhere between 1.0 - 0.1 = 0.9 and 1.0 + 0.1 = 1.1. In other cases, the values are expert estimates, and we only have fuzzy information about the estimation inaccuracy.
This book shows how to compute statistics under such interval and fuzzy uncertainty. The resulting methods are applied to computer science (optimal scheduling of different processors), to information technology (maintaining privacy), to computer engineering (design of computer chips), and to data processing in geosciences, radar imaging, and structural mechanics.
"Sobre este título" puede pertenecer a otra edición de este libro.
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COMPUTING STATISTICS UNDER INTERVAL AND FUZZY UNCERTAINTY: APPLICATIONS TO COMPUTER SCIENCE AND ENGINEERING
Publicado por
Springer, Berlin, 2012
ISBN 10: 3642445705
ISBN 13: 9783642445705
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Librería: Second Story Books, ABAA, Rockville, MD, Estados Unidos de America
Calificación del vendedor: 4 de 5 estrellas
Softcover. Octavo, 430 pages. In Very good condition. Red and blue spine with white lettering. Full binding in red and blue paper. Boards show mild shelf wear and minor edge wear. Text block has light soiling on bottom edge. Note: Shelved in Netdesk Column F, ND-F. 1377680. FP New Rockville Stock. Nº de ref. del artículo: 1377680
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Computing Statistics under Interval and Fuzzy Uncertainty
Publicado por
Springer Berlin Heidelberg, 2014
ISBN 10: 3642445705
ISBN 13: 9783642445705
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Tapa blanda
Librería: moluna, Greven, Alemania
Calificación del vendedor: 4 de 5 estrellas
Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Recent advances in Computing Statistics under Interval and Fuzzy Uncertainty Presents various Applications to Computer Science and Engineering In many practical situations, we are interested in statistics characterizing a population of . Nº de ref. del artículo: 5061326
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Computing Statistics under Interval and Fuzzy Uncertainty: Applications to Computer Science and Engineering (Studies in Computational Intelligence, 393)
Librería: Ria Christie Collections, Uxbridge, Reino Unido
Calificación del vendedor: 5 de 5 estrellas
Condición: New. In. Nº de ref. del artículo: ria9783642445705_new
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Computing Statistics under Interval and Fuzzy Uncertainty
Publicado por
Springer Berlin Heidelberg Jan 2014, 2014
ISBN 10: 3642445705
ISBN 13: 9783642445705
Nuevo
Taschenbuch
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In many practical situations, we are interested in statistics characterizing a population of objects: e.g. in the mean height of people from a certain area. Most algorithms for estimating such statistics assume that the sample values are exact. In practice, sample values come from measurements, and measurements are never absolutely accurate. Sometimes, we know the exact probability distribution of the measurement inaccuracy, but often, we only know the upper bound on this inaccuracy. In this case, we have interval uncertainty: e.g. if the measured value is 1.0, and inaccuracy is bounded by 0.1, then the actual (unknown) value of the quantity can be anywhere between 1.0 - 0.1 = 0.9 and 1.0 + 0.1 = 1.1. In other cases, the values are expert estimates, and we only have fuzzy information about the estimation inaccuracy. This book shows how to compute statistics under such interval and fuzzy uncertainty. The resulting methods are applied to computer science (optimal scheduling of different processors), to information technology (maintaining privacy), to computer engineering (design of computer chips), and to data processing in geosciences, radar imaging, and structural mechanics. 444 pp. Englisch. Nº de ref. del artículo: 9783642445705
Cantidad disponible: 2 disponibles
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Computing Statistics under Interval and Fuzzy Uncertainty : Applications to Computer Science and Engineering
Publicado por
Springer Berlin Heidelberg, 2014
ISBN 10: 3642445705
ISBN 13: 9783642445705
Nuevo
Taschenbuch
Librería: AHA-BUCH GmbH, Einbeck, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - In many practical situations, we are interested in statistics characterizing a population of objects: e.g. in the mean height of people from a certain area. Most algorithms for estimating such statistics assume that the sample values are exact. In practice, sample values come from measurements, and measurements are never absolutely accurate. Sometimes, we know the exact probability distribution of the measurement inaccuracy, but often, we only know the upper bound on this inaccuracy. In this case, we have interval uncertainty: e.g. if the measured value is 1.0, and inaccuracy is bounded by 0.1, then the actual (unknown) value of the quantity can be anywhere between 1.0 - 0.1 = 0.9 and 1.0 + 0.1 = 1.1. In other cases, the values are expert estimates, and we only have fuzzy information about the estimation inaccuracy. This book shows how to compute statistics under such interval and fuzzy uncertainty. The resulting methods are applied to computer science (optimal scheduling of different processors), to information technology (maintaining privacy), to computer engineering (design of computer chips), and to data processing in geosciences, radar imaging, and structural mechanics. Nº de ref. del artículo: 9783642445705
Cantidad disponible: 1 disponibles
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Computing Statistics Under Interval and Fuzzy Uncertainty : Applications to Computer Science and Engineering
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
Calificación del vendedor: 5 de 5 estrellas
Condición: New. Nº de ref. del artículo: 20908509-n
Cantidad disponible: 15 disponibles
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Computing Statistics under Interval and Fuzzy Uncertainty
Publicado por
Springer Berlin Heidelberg, Springer Berlin Heidelberg Jan 2014, 2014
ISBN 10: 3642445705
ISBN 13: 9783642445705
Nuevo
Taschenbuch
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -In many practical situations, we are interested in statistics characterizing a population of objects: e.g. in the mean height of people from a certain area.Most algorithms for estimating such statistics assume that the sample values are exact. In practice, sample values come from measurements, and measurements are never absolutely accurate. Sometimes, we know the exact probability distribution of the measurement inaccuracy, but often, we only know the upper bound on this inaccuracy. In this case, we have interval uncertainty: e.g. if the measured value is 1.0, and inaccuracy is bounded by 0.1, then the actual (unknown) value of the quantity can be anywhere between 1.0 - 0.1 = 0.9 and 1.0 + 0.1 = 1.1. In other cases, the values are expert estimates, and we only have fuzzy information about the estimation inaccuracy.This book shows how to compute statistics under such interval and fuzzy uncertainty. The resulting methods are applied to computer science (optimal scheduling of different processors), to information technology (maintaining privacy), to computer engineering (design of computer chips), and to data processing in geosciences, radar imaging, and structural mechanics.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 444 pp. Englisch. Nº de ref. del artículo: 9783642445705
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Computing Statistics Under Interval and Fuzzy Uncertainty : Applications to Computer Science and Engineering
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
Calificación del vendedor: 5 de 5 estrellas
Condición: As New. Unread book in perfect condition. Nº de ref. del artículo: 20908509
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Computing Statistics under Interval and Fuzzy Uncertainty: Applications to Computer Science and Engineering (Studies in Computational Intelligence, 393)
Librería: Lucky's Textbooks, Dallas, TX, Estados Unidos de America
Calificación del vendedor: 5 de 5 estrellas
Condición: New. Nº de ref. del artículo: ABLIING23Mar3113020228363
Cantidad disponible: Más de 20 disponibles
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Computing Statistics under Interval and Fuzzy Uncertainty (Paperback)
Publicado por
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, Berlin, 2014
ISBN 10: 3642445705
ISBN 13: 9783642445705
Nuevo
Paperback
Librería: Grand Eagle Retail, Mason, OH, Estados Unidos de America
Calificación del vendedor: 5 de 5 estrellas
Paperback. Condición: new. Paperback. In many practical situations, we are interested in statistics characterizing a population of objects: e.g. in the mean height of people from a certain area. Most algorithms for estimating such statistics assume that the sample values are exact. In practice, sample values come from measurements, and measurements are never absolutely accurate. Sometimes, we know the exact probability distribution of the measurement inaccuracy, but often, we only know the upper bound on this inaccuracy. In this case, we have interval uncertainty: e.g. if the measured value is 1.0, and inaccuracy is bounded by 0.1, then the actual (unknown) value of the quantity can be anywhere between 1.0 - 0.1 = 0.9 and 1.0 + 0.1 = 1.1. In other cases, the values are expert estimates, and we only have fuzzy information about the estimation inaccuracy. This book shows how to compute statistics under such interval and fuzzy uncertainty. The resulting methods are applied to computer science (optimal scheduling of different processors), to information technology (maintaining privacy), to computer engineering (design of computer chips), and to data processing in geosciences, radar imaging, and structural mechanics. if the measured value is 1.0, and inaccuracy is bounded by 0.1, then the actual (unknown) value of the quantity can be anywhere between 1.0 - 0.1 = 0.9 and 1.0 + 0.1 = 1.1. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9783642445705
Cantidad disponible: 1 disponibles