Synopsis
Many factors added to the poor quality of services rendered by Global System for Mobile Communication (GSM) operators,one of the factors is call drop.Call drop is also one of the most important key performance indicators (KPI) in measuring customer’s satisfaction. The data obtained from UCL repository was trained with a cortical learning approach to determine the threshold value. The value was compare with value obtained during drive test to determine the quality of network performance. In order to achieve this, six indicators for network performance was used such as network performance is poor and there is a call drop, is excellent, there is no call drop or is fair, call drop may occur. Again the system was able to determine the quality of network performance in the area of study with predictions for call drops using the aforementioned indicators. The results also as explained has proved a novel approach and the prediction will encourages customers’ confidence in the use of different GSM network and will also increase the business potentials of the operators.
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An Intelligent Predictive Model for Call Drop Management
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LAP LAMBERT Academic Publishing Aug 2018, 2018
ISBN 10: 3659592099
ISBN 13: 9783659592096
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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 -Many factors added to the poor quality of services rendered by Global System for Mobile Communication (GSM) operators,one of the factors is call drop.Call drop is also one of the most important key performance indicators (KPI) in measuring customer's satisfaction. The data obtained from UCL repository was trained with a cortical learning approach to determine the threshold value. The value was compare with value obtained during drive test to determine the quality of network performance. In order to achieve this, six indicators for network performance was used such as network performance is poor and there is a call drop, is excellent, there is no call drop or is fair, call drop may occur. Again the system was able to determine the quality of network performance in the area of study with predictions for call drops using the aforementioned indicators. The results also as explained has proved a novel approach and the prediction will encourages customers' confidence in the use of different GSM network and will also increase the business potentials of the operators. 120 pp. Englisch. Seller Inventory # 9783659592096
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An Intelligent Predictive Model for Call Drop Management
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ISBN 10: 3659592099
ISBN 13: 9783659592096
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An Intelligent Predictive Model for Call Drop Management
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ISBN 10: 3659592099
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An Intelligent Predictive Model for Call Drop Management
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ISBN 10: 3659592099
ISBN 13: 9783659592096
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Igbekele Olu AkintayoMasters of Science, Computer Science, University of Port Harcourt, Nigeria. March, 2018.Bachelors of Technology, Computer Science, Federal University of Technology, Akure, Nigeria. November, 2007.Many factors. Seller Inventory # 385767970
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An Intelligent Predictive Model for Call Drop Management
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An Intelligent Predictive Model for Call Drop Management
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ISBN 10: 3659592099
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An Intelligent Predictive Model for Call Drop Management
Published by
LAP LAMBERT Academic Publishing Aug 2018, 2018
ISBN 10: 3659592099
ISBN 13: 9783659592096
New
Taschenbuch
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Taschenbuch. Condition: Neu. Neuware -Many factors added to the poor quality of services rendered by Global System for Mobile Communication (GSM) operators,one of the factors is call drop.Call drop is also one of the most important key performance indicators (KPI) in measuring customer¿s satisfaction. The data obtained from UCL repository was trained with a cortical learning approach to determine the threshold value. The value was compare with value obtained during drive test to determine the quality of network performance. In order to achieve this, six indicators for network performance was used such as network performance is poor and there is a call drop, is excellent, there is no call drop or is fair, call drop may occur. Again the system was able to determine the quality of network performance in the area of study with predictions for call drops using the aforementioned indicators. The results also as explained has proved a novel approach and the prediction will encourages customers¿ confidence in the use of different GSM network and will also increase the business potentials of the operators.Books on Demand GmbH, Überseering 33, 22297 Hamburg 120 pp. Englisch. Seller Inventory # 9783659592096
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An Intelligent Predictive Model for Call Drop Management
Published by
LAP LAMBERT Academic Publishing, 2018
ISBN 10: 3659592099
ISBN 13: 9783659592096
New
Taschenbuch
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Many factors added to the poor quality of services rendered by Global System for Mobile Communication (GSM) operators,one of the factors is call drop.Call drop is also one of the most important key performance indicators (KPI) in measuring customer's satisfaction. The data obtained from UCL repository was trained with a cortical learning approach to determine the threshold value. The value was compare with value obtained during drive test to determine the quality of network performance. In order to achieve this, six indicators for network performance was used such as network performance is poor and there is a call drop, is excellent, there is no call drop or is fair, call drop may occur. Again the system was able to determine the quality of network performance in the area of study with predictions for call drops using the aforementioned indicators. The results also as explained has proved a novel approach and the prediction will encourages customers' confidence in the use of different GSM network and will also increase the business potentials of the operators. Seller Inventory # 9783659592096
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An Intelligent Predictive Model for Call Drop Management
Published by
LAP LAMBERT Academic Publishing, 2018
ISBN 10: 3659592099
ISBN 13: 9783659592096
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