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Title: Erlang B traffic table modeled as an artificial neuronal network in an application for Smartphone
Authors: Johan Julián Molina Mosquera, José de Jesús Salgado Patrón, Faiber Robayo Betancourt
Journal: ARPN Journal of Engineering and Applied Sciences
Publisher: Khyber Medical College, Peshawar
Country: Pakistan
Year: 2021
Volume: 16
Issue: 17
Language: English
This paper presents the methodology to implement the non-linear function of Erlang B as a multilayer ANN (Artificial Neural Network). The number of channels and the traffic intensity of the system are used as input parameters, and the blocking probability or degree of service is used as output data. The proposed model allows the development of the view controller model of the native Android application, in which another variable is entered corresponding to the intensity of traffic per user. The Android app showed results with an error of 0.06%, storing the data to visualize them graphically, thus allowing to simulate and analyze the traffic of fixed telephony and mobile telephony systems.
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