… , machine learning predictors can be viable alternative. Hence there is need to explore
performance of machine learning predictors for mobility prediction in … powerful machine learning …

… predict the location of mobile users in order to act proactively. We focus on the location
prediction … of the spatial trajectories through the adoption of Machine Learning (ML) techniques. …

… In this paper, a centralized routing scheme with mobility prediction … mobility prediction
through advanced artificial neural network (ANN) technique. Then, based on the mobility prediction…

… DATASET DESCRIPTION In order to evaluate the performance of the mobility prediction
framework, we adopt two types of datasets (ie, a model-based dataset and a realistic dataset) …

… for mobility prediction in a large-scale train network. Our proposed mobility prediction model
overcomes … Based on the intelligence gained from the mobility model, ie, mobility prediction …

… Then, Support Vector Machine (SVM) algorithm is the ML algorithm we … mobility prediction
and introduce a future work plan where mobility prediction will be applied for improving mobile …

… Mobility prediction is a technique in which the future location of a user is identified in a
given network. Mobility prediction … and to recalculate paths in Mobile Ad hoc Networks (MANET). …

… , each mobile node is assumed to know its current mobility … mobility prediction based on
several standard mobility models. … mobility models illustrate how the proposed prediction method …

… mobility data was constructed with multiple machine learning … Our results showed that, for
selected counties, the mobility … , and the weekly pattern of mobility and infections implied high …

… mobility predictions (eg, travel demand/traffic flows), but no review study on the individual
mobility prediction… existing studies on individual mobility prediction in transport (data/problem/…