Synopsis
Forecasting is a common statistical task in many areas, where it contributes to inform decisions about the scheduling of production, transportation, personnel, etc. And it provides a guide to long-term strategic planning. In many areas such as financial, energy, economics, the time series data are non-stationary, contain trend and seasonal variations. The goal of this thesis is to forecast the time series using two approaches, namely the statistical approaches; they are seasonal ARIMA, seasonal VARIMA models and Neural Networks approach and compare them in order to find the best model for time series forecasting. The energy area has an important role in the development of countries; thus, consumption planning of energy must be made accurately, despite they are governed by other factors such as that population, gross domestic product, weather vagaries, storage capacity, etc.
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About the Author
Abdoulaye Camara, Master Department of Information and Computing Science, School of Mathematics and Physics,University of Science and Technology Beijing, China
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Time Series Forecasting Using Statistical And Neural Networks Models
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LAP LAMBERT Academic Publishing Sep 2016, 2016
ISBN 10: 3659944742
ISBN 13: 9783659944741
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Forecasting is a common statistical task in many areas, where it contributes to inform decisions about the scheduling of production, transportation, personnel, etc. And it provides a guide to long-term strategic planning. In many areas such as financial, energy, economics, the time series data are non-stationary, contain trend and seasonal variations. The goal of this thesis is to forecast the time series using two approaches, namely the statistical approaches; they are seasonal ARIMA, seasonal VARIMA models and Neural Networks approach and compare them in order to find the best model for time series forecasting. The energy area has an important role in the development of countries; thus, consumption planning of energy must be made accurately, despite they are governed by other factors such as that population, gross domestic product, weather vagaries, storage capacity, etc. 120 pp. Englisch. Seller Inventory # 9783659944741
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Time Series Forecasting Using Statistical And Neural Networks Models
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Camara AbdoulayeAbdoulaye Camara, Master Department of Information and Computing Science, School of Mathematics and Physics,University of Science and Technology Beijing, ChinaForecasting is a common statistical task in many areas. Seller Inventory # 153342469
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Time Series Forecasting Using Statistical And Neural Networks Models
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Time Series Forecasting Using Statistical And Neural Networks Models
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LAP LAMBERT Academic Publishing Sep 2016, 2016
ISBN 10: 3659944742
ISBN 13: 9783659944741
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Forecasting is a common statistical task in many areas, where it contributes to inform decisions about the scheduling of production, transportation, personnel, etc. And it provides a guide to long-term strategic planning. In many areas such as financial, energy, economics, the time series data are non-stationary, contain trend and seasonal variations. The goal of this thesis is to forecast the time series using two approaches, namely the statistical approaches; they are seasonal ARIMA, seasonal VARIMA models and Neural Networks approach and compare them in order to find the best model for time series forecasting. The energy area has an important role in the development of countries; thus, consumption planning of energy must be made accurately, despite they are governed by other factors such as that population, gross domestic product, weather vagaries, storage capacity, etc.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 120 pp. Englisch. Seller Inventory # 9783659944741
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Time Series Forecasting Using Statistical And Neural Networks Models
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LAP LAMBERT Academic Publishing, 2016
ISBN 10: 3659944742
ISBN 13: 9783659944741
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Forecasting is a common statistical task in many areas, where it contributes to inform decisions about the scheduling of production, transportation, personnel, etc. And it provides a guide to long-term strategic planning. In many areas such as financial, energy, economics, the time series data are non-stationary, contain trend and seasonal variations. The goal of this thesis is to forecast the time series using two approaches, namely the statistical approaches; they are seasonal ARIMA, seasonal VARIMA models and Neural Networks approach and compare them in order to find the best model for time series forecasting. The energy area has an important role in the development of countries; thus, consumption planning of energy must be made accurately, despite they are governed by other factors such as that population, gross domestic product, weather vagaries, storage capacity, etc. Seller Inventory # 9783659944741
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Time Series Forecasting Using Statistical And Neural Networks Models
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ISBN 10: 3659944742
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Taschenbuch. Condition: Neu. Time Series Forecasting Using Statistical And Neural Networks Models | Abdoulaye Camara | Taschenbuch | 120 S. | Englisch | 2016 | LAP LAMBERT Academic Publishing | EAN 9783659944741 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Seller Inventory # 103010180