“Aplicación móvil inteligente para la predicción de la pérdida de señal en redes de telecomunicación a partir de variables meteorológicas - Aguilar Zambrano, Angie Sthepanie (2017)
The aim of this research project is to develop a mobile application to predict signal loss in terms of meteorological variables, serving as support for decision-making by telecommunication specialists. For the development of the project was used the information of previous research. During the project a pre-processing of the data was performed; removing outliers and correlations between variables. Also, different data mining classification techniques were analyzed using an optimization approach. As a result, it was determined that the classification algorithm based on Artificial Neural Networks turns out to be the most accurate with an accuracy level of 100%. With aims of applying the classification model obtained during the process of data mining in real-life scenarios, it was represented using the PMML language and subsequently processed with Java technology for the development of a mobile application. The application is named SignalPred and predicts possible signal losses from both manual and automated reading of meteorological variables.