  Smartphones have been the most popular and widely used devices among means of
communication. Nowadays, human activity recognition is possible on mobile
devices by embedded sensors, which can be exploited to manage user behavior on
mobile devices by predicting user activity. To reach this aim, storing activity
characteristics, Classification, and mapping them to a learning algorithm was
studied in this research. In this study, we applied categorization through deep
belief network to test and training data, which resulted in 98.25% correct
diagnosis in training data and 93.01% in test data. Therefore, in this study,
we prove that the deep belief network is a suitable method for this particular
purpose.
