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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 - Brossura
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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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L'autore
Robert 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, Vodafone Egypt and Intel Egypt. He participated and obtained the first rank in the NN5 Forecasting Competition for Neural Networks.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
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Advanced Forecasting Techniques with Application to NN5 Time Series
Editore:
LAP LAMBERT Academic Publishing, 2012
ISBN 10: 3659129623
ISBN 13: 9783659129629
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Da: moluna, Greven, Germania
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Condizione: 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. Codice articolo 5133536
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Advanced Forecasting Techniques with Application to NN5 Time Series
Editore:
LAP LAMBERT Academic Publishing Aug 2012, 2012
ISBN 10: 3659129623
ISBN 13: 9783659129629
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
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Taschenbuch. Condizione: 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. Codice articolo 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
Editore:
LAP LAMBERT Academic Publishing, 2012
ISBN 10: 3659129623
ISBN 13: 9783659129629
Nuovo
Taschenbuch
Da: AHA-BUCH GmbH, Einbeck, Germania
Valutazione del venditore 5 su 5 stelle
Taschenbuch. Condizione: 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. Codice articolo 9783659129629
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Immagini fornite dal venditore
Advanced Forecasting Techniques with Application to NN5 Time Series
Editore:
LAP LAMBERT Academic Publishing Aug 2012, 2012
ISBN 10: 3659129623
ISBN 13: 9783659129629
Nuovo
Taschenbuch
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
Valutazione del venditore 5 su 5 stelle
Taschenbuch. Condizione: Neu. 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.Books on Demand GmbH, Überseering 33, 22297 Hamburg 132 pp. Englisch. Codice articolo 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
Editore:
LAP LAMBERT Academic Publishing, 2012
ISBN 10: 3659129623
ISBN 13: 9783659129629
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Da: Mispah books, Redhill, SURRE, Regno Unito
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Paperback. Condizione: Like New. Like New. book. Codice articolo ERICA77536591296236
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