A Proposed Predictive Analytics Model for ITDSS: Intelligent Transportation Decision Support System - Softcover
Inhaltsangabe
Although relying on Predictive Analytics (PA) in our digital transformation age becomes an important way to achieve success, the public enterprise sector companies specialized in passenger intercity transportation in Egypt still rely on descriptive reports and unsupported opinions in transportation planning. Therefore, these companies need to rely on PA in the transportation planning and decision-making process. Moving toward PA is a clear path to become an intelligent organization. The use of PA does not only drive cost-saving and revenue growth but also provides more accurate and timely information to develop the decision-making process and achieve various strategic objectives. Ridership prediction is one of the most important prediction studies that could be performed in intercity public transportation companies. It is considered at the heart of transportation policymaking and the success of transportation systems because it affects the revenue of the company. The main goal of this book is to build a predictive analytics machine learning ridership model to aid Upper Egypt Company (UE Co.) planners depend on analytics to replace unsupported opinions with data-driven conclusions.
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Über die Autorin bzw. den Autor
Radwa Mohamed Elsofy Senior Researcher in the Egyptian Tax Authority (ETA). Doctor of Information Systems and Computers..Member of the Board of Directors and Treasurer of the Egyptian Society for Information Systems and Computer Technology (ESISACT).
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A Proposed Predictive Analytics Model for ITDSS
Verlag:
LAP LAMBERT Academic Publishing Apr 2022, 2022
ISBN 10: 6200303959
ISBN 13: 9786200303950
Neu
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Although relying on Predictive Analytics (PA) in our digital transformation age becomes an important way to achieve success, the public enterprise sector companies specialized in passenger intercity transportation in Egypt still rely on descriptive reports and unsupported opinions in transportation planning. Therefore, these companies need to rely on PA in the transportation planning and decision-making process. Moving toward PA is a clear path to become an intelligent organization. The use of PA does not only drive cost-saving and revenue growth but also provides more accurate and timely information to develop the decision-making process and achieve various strategic objectives. Ridership prediction is one of the most important prediction studies that could be performed in intercity public transportation companies. It is considered at the heart of transportation policymaking and the success of transportation systems because it affects the revenue of the company. The main goal of this book is to build a predictive analytics machine learning ridership model to aid Upper Egypt Company (UE Co.) planners depend on analytics to replace unsupported opinions with data-driven conclusions. 260 pp. Englisch. Bestandsnummer des Verkäufers 9786200303950
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A Proposed Predictive Analytics Model for ITDSS: Intelligent Transportation Decision Support System
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LAP LAMBERT Academic Publishing, 2022
ISBN 10: 6200303959
ISBN 13: 9786200303950
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A Proposed Predictive Analytics Model for ITDSS
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ISBN 13: 9786200303950
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Although relying on Predictive Analytics (PA) in our digital transformation age becomes an important way to achieve success, the public enterprise sector companies specialized in passenger intercity transportation in Egypt still rely on descriptive reports . Bestandsnummer des Verkäufers 601137756
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A Proposed Predictive Analytics Model for ITDSS: Intelligent Transportation Decision Support System
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LAP LAMBERT Academic Publishing, 2022
ISBN 10: 6200303959
ISBN 13: 9786200303950
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A Proposed Predictive Analytics Model for ITDSS: Intelligent Transportation Decision Support System
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LAP LAMBERT Academic Publishing, 2022
ISBN 10: 6200303959
ISBN 13: 9786200303950
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A Proposed Predictive Analytics Model for ITDSS
Verlag:
LAP LAMBERT Academic Publishing Apr 2022, 2022
ISBN 10: 6200303959
ISBN 13: 9786200303950
Neu
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Taschenbuch. Zustand: Neu. Neuware -Although relying on Predictive Analytics (PA) in our digital transformation age becomes an important way to achieve success, the public enterprise sector companies specialized in passenger intercity transportation in Egypt still rely on descriptive reports and unsupported opinions in transportation planning. Therefore, these companies need to rely on PA in the transportation planning and decision-making process. Moving toward PA is a clear path to become an intelligent organization. The use of PA does not only drive cost-saving and revenue growth but also provides more accurate and timely information to develop the decision-making process and achieve various strategic objectives. Ridership prediction is one of the most important prediction studies that could be performed in intercity public transportation companies. It is considered at the heart of transportation policymaking and the success of transportation systems because it affects the revenue of the company. The main goal of this book is to build a predictive analytics machine learning ridership model to aid Upper Egypt Company (UE Co.) planners depend on analytics to replace unsupported opinions with data-driven conclusions.Books on Demand GmbH, Überseering 33, 22297 Hamburg 260 pp. Englisch. Bestandsnummer des Verkäufers 9786200303950
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Beispielbild für diese ISBN
A Proposed Predictive Analytics Model for ITDSS : Intelligent Transportation Decision Support System
Verlag:
LAP LAMBERT Academic Publishing, 2022
ISBN 10: 6200303959
ISBN 13: 9786200303950
Neu
Taschenbuch
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Although relying on Predictive Analytics (PA) in our digital transformation age becomes an important way to achieve success, the public enterprise sector companies specialized in passenger intercity transportation in Egypt still rely on descriptive reports and unsupported opinions in transportation planning. Therefore, these companies need to rely on PA in the transportation planning and decision-making process. Moving toward PA is a clear path to become an intelligent organization. The use of PA does not only drive cost-saving and revenue growth but also provides more accurate and timely information to develop the decision-making process and achieve various strategic objectives. Ridership prediction is one of the most important prediction studies that could be performed in intercity public transportation companies. It is considered at the heart of transportation policymaking and the success of transportation systems because it affects the revenue of the company. The main goal of this book is to build a predictive analytics machine learning ridership model to aid Upper Egypt Company (UE Co.) planners depend on analytics to replace unsupported opinions with data-driven conclusions. Bestandsnummer des Verkäufers 9786200303950
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