Articles liés à Intelligent Systems and Financial Forecasting
Synopsis
This book examines the design of an automated system for financial time series forecasting. It explores the level of automation which can be achieved by a system for modelling a given financial time series with the minimum of human intervention. It aims t
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This book examines the design of an automated system for financial time series forecasting. It explores the level of automation which can be achieved by a system for modelling a given financial time series with the minimum of human intervention. It aims t
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Intelligent Systems and Financial Forecasting
Edité par
Springer, 1997
ISBN 10 : 3540760989
ISBN 13 : 9783540760986
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Etat : Good. Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Ex-library, so some stamps and wear, but in good overall condition. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions. N° de réf. du vendeur Z1-U-022-01655
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Intelligent Systems and Financial Forecasting (Perspectives in Neural Computing)
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Springer-Verlag Berlin and Heidelberg GmbH & Co. K, 1997
ISBN 10 : 3540760989
ISBN 13 : 9783540760986
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Taschenbuch. Etat : Gut. 227 Seiten ex Library Book / aus einer wissenschaftlichen Bibliothek Sprache: Englisch Gewicht in Gramm: 341. N° de réf. du vendeur 277762
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Intelligent Systems and Financial Forecasting
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Springer London, 1997
ISBN 10 : 3540760989
ISBN 13 : 9783540760986
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Couverture souple
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Intelligent Systems and Financial Forecasting
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Springer, 1997
ISBN 10 : 3540760989
ISBN 13 : 9783540760986
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Intelligent Systems and Financial Forecasting
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Intelligent Systems and Financial Forecasting
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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - A fundamental objective of Artificial Intelligence (AI) is the creation of in telligent computer programs. In more modest terms AI is simply con cerned with expanding the repertoire of computer applications into new domains and to new levels of efficiency. The motivation for this effort comes from many sources. At a practical level there is always a demand for achieving things in more efficient ways. Equally, there is the technical challenge of building programs that allow a machine to do something a machine has never done before. Both of these desires are contained within AI and both provide the inspirational force behind its development. In terms of satisfying both of these desires there can be no better example than machine learning. Machines that can learn have an in-built effi ciency. The same software can be applied in many applications and in many circumstances. The machine can adapt its behaviour so as to meet the demands of new, or changing, environments without the need for costly re-programming. In addition, a machine that can learn can be ap plied in new domains with the genuine potential for innovation. In this sense a machine that can learn can be applied in areas where little is known about possible causal relationships, and even in circumstances where causal relationships are judged not to exist. This last aspect is of major significance when considering machine learning as applied to fi nancial forecasting. N° de réf. du vendeur 9783540760986
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Intelligent Systems and Financial Forecasting
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Intelligent Systems and Financial Forecasting
Edité par
Springer London, Springer Berlin Heidelberg Apr 1997, 1997
ISBN 10 : 3540760989
ISBN 13 : 9783540760986
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Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -A fundamental objective of Artificial Intelligence (AI) is the creation of in telligent computer programs. In more modest terms AI is simply con cerned with expanding the repertoire of computer applications into new domains and to new levels of efficiency. The motivation for this effort comes from many sources. At a practical level there is always a demand for achieving things in more efficient ways. Equally, there is the technical challenge of building programs that allow a machine to do something a machine has never done before. Both of these desires are contained within AI and both provide the inspirational force behind its development. In terms of satisfying both of these desires there can be no better example than machine learning. Machines that can learn have an in-built effi ciency. The same software can be applied in many applications and in many circumstances. The machine can adapt its behaviour so as to meet the demands of new, or changing, environments without the need for costly re-programming. In addition, a machine that can learn can be ap plied in new domains with the genuine potential for innovation. In this sense a machine that can learn can be applied in areas where little is known about possible causal relationships, and even in circumstances where causal relationships are judged not to exist. This last aspect is of major significance when considering machine learning as applied to fi nancial forecasting.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 240 pp. Englisch. N° de réf. du vendeur 9783540760986
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Intelligent Systems and Financial Forecasting
Edité par
Springer London Apr 1997, 1997
ISBN 10 : 3540760989
ISBN 13 : 9783540760986
Neuf
Taschenbuch
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -A fundamental objective of Artificial Intelligence (AI) is the creation of in telligent computer programs. In more modest terms AI is simply con cerned with expanding the repertoire of computer applications into new domains and to new levels of efficiency. The motivation for this effort comes from many sources. At a practical level there is always a demand for achieving things in more efficient ways. Equally, there is the technical challenge of building programs that allow a machine to do something a machine has never done before. Both of these desires are contained within AI and both provide the inspirational force behind its development. In terms of satisfying both of these desires there can be no better example than machine learning. Machines that can learn have an in-built effi ciency. The same software can be applied in many applications and in many circumstances. The machine can adapt its behaviour so as to meet the demands of new, or changing, environments without the need for costly re-programming. In addition, a machine that can learn can be ap plied in new domains with the genuine potential for innovation. In this sense a machine that can learn can be applied in areas where little is known about possible causal relationships, and even in circumstances where causal relationships are judged not to exist. This last aspect is of major significance when considering machine learning as applied to fi nancial forecasting. 240 pp. Englisch. N° de réf. du vendeur 9783540760986
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Intelligent Systems and Financial Forecasting
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