Wireless user estimation using artificial neural networks
Daniel Abinoja, Rhen Anjerome Bedruz, Kevin Loo Jovellanos, Argel Alejandro Bandala · 2015
Mobile devices, with the improving trend of smartphone use, is an area of study for human behavior on wireless data communications systems which serves as the converging focal point. The prediction of user quantities with non-intrusive data gathering in wireless communications trends and the correlation of Wi-Fi characteristics with quantity are important links towards data aggregation technique developments. To estimate user load in wireless connection systems, multi-layer feed forward artificial neural network based on BP algorithm is proposed and implemented with MATLAB to aid in optimization of performance in such networks. Error calculation, test, validation, and training performance are evaluated for the algorithm's applicability.