… In the field of individual mobility prediction, existing works can be classified into two categories:
… on three real-world mobility datasets with simulated multi-user environment and conduct …

… use Deep Learning (DL) approaches to solve mobility-related challenges. In this survey, we
focus on DL solutions to predict … : (i) as a multi-class classification task, in which we have as …

… Therefore, we first roughly classify … In this paper, we focus on the fine-grained prediction
of user consumption, that is, the prediction of user call consumption and traffic consumption. …

… Another aspect of our study was the use of various classification algorithms in conjunction
… Furthermore, we used a nonparametric decision tree to classify both categorical and …

… diagnose the cardiovascular disease and classify into five available … on the classified data
via user mobile application which … accuracy for prediction and classification of cardiac disease. …

… Third, we focus on three kinds of traffic prediction problems (ie, classification, … prediction
problem means. Therefore, we will use some examples to show the concept of traffic prediction…

… users’ phone call assistive services by effectively predicting … to effectively predict individual
mobile phone users behavior … the existing classification approaches, the prediction accuracy (…

… from human mobility patterns is one of the … mobility patterns and urban functions. However,
few studies have fully leveraged traffic interaction information that is hidden in human mobility …

… data of users, with their online habits and behaviors, could predict their voting intentions;
it … In the present study, this included the classification of the main massive data collection …

… the aggregated features and predicting the bounding box, prediction score classifies into …
crop, the user can either select the image from the mobile already saved in the mobile gallery, …