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Advanced Forecasting Techniques with Application to NN5 Time Series: New Bayesian Formulation for Holt's Exponential Smoothing and Comparison of Forecasting Combination Techniques - Couverture souple
Synopsis
In this book we analyze the forecasting model that achieved the first rank in the Forecasting Competition for Artificial Neural Networks & Computational Intelligence NN5. The model is based on combination of machine learning and linear models. In addition, the approach and the experiments done to develop this model are explained in details to allow the reader to learn the methodology of developing such optimal models. The book also introduces a Bayesian forecasting approach for Holt's additive exponential smoothing method. Starting from the state space formulation, a formula for the forecast is derived and reduced to a two-dimensional integration that can be computed numerically in a straightforward way. In contrast with much of the work for exponential smoothing, this method produces the forecast density as well. The combinations of forecast are investigated as well in this book. A comparison between different combination methods is introduced with complete case study on tourism demand forecasting in Egypt.
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- ÉditeurLAP LAMBERT Academic Publishing
- Date d'édition2012
- ISBN 10 3659129623
- ISBN 13 9783659129629
- ReliureBroché
- Langueanglais
- Nombre de pages132
- Coordonnées du fabricantnon disponible
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Advanced Forecasting Techniques with Application to NN5 Time Series
Edité par
LAP LAMBERT Academic Publishing, 2012
ISBN 10 : 3659129623
ISBN 13 : 9783659129629
Neuf
Couverture souple
Vendeur : moluna, Greven, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Andrawis RobertRobert R. Andrawis, Received his B.S. and Master degree in 2006 and 2010 respectively from the Department of Computer Engineering, Cairo University, Egypt. He also worked in Egyptian Ministry of Communication, Valeo, V. N° de réf. du vendeur 5133536
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Advanced Forecasting Techniques with Application to NN5 Time Series : New Bayesian Formulation for Holt's Exponential Smoothing and Comparison of Forecasting Combination Techniques
Edité par
LAP LAMBERT Academic Publishing, 2012
ISBN 10 : 3659129623
ISBN 13 : 9783659129629
Neuf
Taschenbuch
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In this book we analyze the forecasting model that achieved the first rank in the Forecasting Competition for Artificial Neural Networks & Computational Intelligence NN5. The model is based on combination of machine learning and linear models. In addition, the approach and the experiments done to develop this model are explained in details to allow the reader to learn the methodology of developing such optimal models. The book also introduces a Bayesian forecasting approach for Holt's additive exponential smoothing method. Starting from the state space formulation, a formula for the forecast is derived and reduced to a two-dimensional integration that can be computed numerically in a straightforward way. In contrast with much of the work for exponential smoothing, this method produces the forecast density as well. The combinations of forecast are investigated as well in this book. A comparison between different combination methods is introduced with complete case study on tourism demand forecasting in Egypt. N° de réf. du vendeur 9783659129629
Quantité disponible : 1 disponible(s)
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Advanced Forecasting Techniques with Application to NN5 Time Series
Edité par
LAP LAMBERT Academic Publishing Aug 2012, 2012
ISBN 10 : 3659129623
ISBN 13 : 9783659129629
Neuf
Taschenbuch
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In this book we analyze the forecasting model that achieved the first rank in the Forecasting Competition for Artificial Neural Networks & Computational Intelligence NN5. The model is based on combination of machine learning and linear models. In addition, the approach and the experiments done to develop this model are explained in details to allow the reader to learn the methodology of developing such optimal models. The book also introduces a Bayesian forecasting approach for Holt's additive exponential smoothing method. Starting from the state space formulation, a formula for the forecast is derived and reduced to a two-dimensional integration that can be computed numerically in a straightforward way. In contrast with much of the work for exponential smoothing, this method produces the forecast density as well. The combinations of forecast are investigated as well in this book. A comparison between different combination methods is introduced with complete case study on tourism demand forecasting in Egypt. 132 pp. Englisch. N° de réf. du vendeur 9783659129629
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Advanced Forecasting Techniques with Application to NN5 Time Series: New Bayesian Formulation for Holt*s Exponential Smoothing and Comparison of Forecasting Combination Techniques
Edité par
LAP LAMBERT Academic Publishing, 2012
ISBN 10 : 3659129623
ISBN 13 : 9783659129629
Ancien ou d'occasion
Paperback
Vendeur : Mispah books, Redhill, SURRE, Royaume-Uni
Évaluation du vendeur 4 sur 5 étoiles
Paperback. Etat : Like New. Like New. book. N° de réf. du vendeur ERICA77536591296236
Quantité disponible : 1 disponible(s)