intelligent predictive model call von igbekele olu (10 Ergebnisse)

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Paperback. Zustand: Brand New. 120 pages. 8.66x5.91x0.28 inches. In Stock.

Taschenbuch. Zustand: 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.

Taschenbuch. Zustand: Neu. An Intelligent Predictive Model for Call Drop Management | Akintayo Igbekele Olu (u. a.) | Taschenbuch | 120 S. | Englisch | 2018 | LAP LAMBERT Academic Publishing | EAN 9783659592096 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.

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Taschenbuch. Zustand: 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.

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Zustand: 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.

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Taschenbuch. Zustand: 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.