Aerial Threat Perception Using Data Mining: Solution to predict all air based threats using Data Mining - Softcover
Synopsis
This book presents a design framework based on a centralized scalable architecture for effective simulated aerial threat perception. In this framework data mining and pattern classification techniques are incorporated. This paper focuses on effective prediction by relying on the knowledge base and finding patterns for building the decision trees. This framework is flexibly designed to seamlessly integrate with other applications. The results show the effectiveness of selected algorithms and suggest that more the parameters are incorporated for the decision making for aerial threats; the better is our confidence level on the results. To delve into accurate target prediction we have to make decisions on multiple factors. Multiple techniques used together helps in finding the accurate threat classification and result in better confidence on our results.
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About the Author
M. Anwar-ul-Haq is a Lecturer at Foundation University, Islamabad. He completed his Masters in Software Engineering from National University of Science and Technology, Islamabad Pakistan and graduation from Ghulam Ishaq Khan Institute, Topi Khyber Pakhtunkhwa, Pakistan. His research interests include Machine Learning & Data Mining.
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Aerial Threat Perception Using Data Mining
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LAP LAMBERT Academic Publishing Mai 2011, 2011
ISBN 10: 3844393722
ISBN 13: 9783844393729
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Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents a design framework based on a centralized scalable architecture for effective simulated aerial threat perception. In this framework data mining and pattern classification techniques are incorporated. This paper focuses on effective prediction by relying on the knowledge base and finding patterns for building the decision trees. This framework is flexibly designed to seamlessly integrate with other applications. The results show the effectiveness of selected algorithms and suggest that more the parameters are incorporated for the decision making for aerial threats; the better is our confidence level on the results. To delve into accurate target prediction we have to make decisions on multiple factors. Multiple techniques used together helps in finding the accurate threat classification and result in better confidence on our results. 72 pp. Englisch. Seller Inventory # 9783844393729
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Aerial Threat Perception Using Data Mining
Published by
LAP LAMBERT Academic Publishing, 2011
ISBN 10: 3844393722
ISBN 13: 9783844393729
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Seller: moluna, Greven, Germany
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Anwar-ul-Haq MuhammadM. Anwar-ul-Haq is a Lecturer at Foundation University, Islamabad. He completed his Masters in Software Engineering from National University of Science and Technology, Islamabad Pakistan and graduation from Gh. Seller Inventory # 5476851
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Aerial Threat Perception Using Data Mining
Published by
LAP LAMBERT Academic Publishing Mai 2011, 2011
ISBN 10: 3844393722
ISBN 13: 9783844393729
New
Taschenbuch
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book presents a design framework based on a centralized scalable architecture for effective simulated aerial threat perception. In this framework data mining and pattern classification techniques are incorporated. This paper focuses on effective prediction by relying on the knowledge base and finding patterns for building the decision trees. This framework is flexibly designed to seamlessly integrate with other applications. The results show the effectiveness of selected algorithms and suggest that more the parameters are incorporated for the decision making for aerial threats; the better is our confidence level on the results. To delve into accurate target prediction we have to make decisions on multiple factors. Multiple techniques used together helps in finding the accurate threat classification and result in better confidence on our results.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 72 pp. Englisch. Seller Inventory # 9783844393729
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Aerial Threat Perception Using Data Mining : Solution to predict all air based threats using Data Mining
Published by
LAP LAMBERT Academic Publishing, 2011
ISBN 10: 3844393722
ISBN 13: 9783844393729
New
Taschenbuch
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book presents a design framework based on a centralized scalable architecture for effective simulated aerial threat perception. In this framework data mining and pattern classification techniques are incorporated. This paper focuses on effective prediction by relying on the knowledge base and finding patterns for building the decision trees. This framework is flexibly designed to seamlessly integrate with other applications. The results show the effectiveness of selected algorithms and suggest that more the parameters are incorporated for the decision making for aerial threats; the better is our confidence level on the results. To delve into accurate target prediction we have to make decisions on multiple factors. Multiple techniques used together helps in finding the accurate threat classification and result in better confidence on our results. Seller Inventory # 9783844393729
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Aerial Threat Perception Using Data Mining | Solution to predict all air based threats using Data Mining
Published by
LAP LAMBERT Academic Publishing, 2011
ISBN 10: 3844393722
ISBN 13: 9783844393729
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Seller: preigu, Osnabrück, Germany
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Taschenbuch. Condition: Neu. Aerial Threat Perception Using Data Mining | Solution to predict all air based threats using Data Mining | Muhammad Anwar-Ul-Haq | Taschenbuch | 72 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783844393729 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. Seller Inventory # 107015510