Language: English
Published by LAP LAMBERT Academic Publishing, 2019
ISBN 10: 3659552402 ISBN 13: 9783659552403
Seller: Books Puddle, New York, NY, U.S.A.
Condition: New.
Language: English
Published by LAP LAMBERT Academic Publishing, 2019
ISBN 10: 3659552402 ISBN 13: 9783659552403
Seller: Revaluation Books, Exeter, United Kingdom
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Add to basketPaperback. Condition: Brand New. 52 pages. 8.66x5.91x0.12 inches. In Stock.
Language: English
Published by LAP LAMBERT Academic Publishing, 2019
ISBN 10: 3659552402 ISBN 13: 9783659552403
Seller: preigu, Osnabrück, Germany
Taschenbuch. Condition: Neu. Introducing a new hybrid modelling for forecasting | Mohsen Tavan | Taschenbuch | 52 S. | Englisch | 2019 | LAP LAMBERT Academic Publishing | EAN 9783659552403 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
Language: English
Published by LAP LAMBERT Academic Publishing Jul 2019, 2019
ISBN 10: 3659552402 ISBN 13: 9783659552403
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The purpose of this book is to introduce a new hybrid modelling to predict carbon dioxide emissions in order to make the correct decision to reduce air pollution in Iran. While there are not many data available for some variables, in this modeling, the goal is to make accurate predictions even with low data. In the present book, CO2 emissions in Iran in the period of 1980-2014 was predicted using three models of Auto-Regressive Distributed Lag (ARDL), Fuzzy Linear Regression (FLR) and hybrid model based on a combination of ARDL and FLR models, and then the prediction accuracy of the models is compared. 52 pp. Englisch.
Language: English
Published by LAP LAMBERT Academic Publishing, 2019
ISBN 10: 3659552402 ISBN 13: 9783659552403
Seller: Majestic Books, Hounslow, United Kingdom
Condition: New. Print on Demand.
Language: English
Published by LAP LAMBERT Academic Publishing, 2019
ISBN 10: 3659552402 ISBN 13: 9783659552403
Seller: Biblios, Frankfurt am main, HESSE, Germany
Condition: New. PRINT ON DEMAND.
Language: English
Published by LAP LAMBERT Academic Publishing, 2019
ISBN 10: 3659552402 ISBN 13: 9783659552403
Seller: moluna, Greven, Germany
Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Tavan MohsenThe author of this book has a Bachelor in Business Economics from Lorestan University and an MA in Energy Economics from the Persian Gulf university and more than 10 ISC International Papers.The purpose of this book i.
Language: English
Published by LAP LAMBERT Academic Publishing Jul 2019, 2019
ISBN 10: 3659552402 ISBN 13: 9783659552403
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The purpose of this book is to introduce a new hybrid modelling to predict carbon dioxide emissions in order to make the correct decision to reduce air pollution in Iran. While there are not many data available for some variables, in this modeling, the goal is to make accurate predictions even with low data. In the present book, CO2 emissions in Iran in the period of 1980-2014 was predicted using three models of Auto-Regressive Distributed Lag (ARDL), Fuzzy Linear Regression (FLR) and hybrid model based on a combination of ARDL and FLR models, and then the prediction accuracy of the models is compared.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 52 pp. Englisch.
Language: English
Published by LAP LAMBERT Academic Publishing, 2019
ISBN 10: 3659552402 ISBN 13: 9783659552403
Seller: AHA-BUCH GmbH, Einbeck, Germany
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The purpose of this book is to introduce a new hybrid modelling to predict carbon dioxide emissions in order to make the correct decision to reduce air pollution in Iran. While there are not many data available for some variables, in this modeling, the goal is to make accurate predictions even with low data. In the present book, CO2 emissions in Iran in the period of 1980-2014 was predicted using three models of Auto-Regressive Distributed Lag (ARDL), Fuzzy Linear Regression (FLR) and hybrid model based on a combination of ARDL and FLR models, and then the prediction accuracy of the models is compared.