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Suppose $A$ and $B$ are two stations within the mass rapid transit network of a city. Both stations see approximately the same average daily number of passengers entering and exiting their gates. However, passengers are evenly distributed…

Activity-based models appeared as an answer to the limitations of the traditional trip-based and tour-based four-stage models. The fundamental assumption of activity-based models is that travel demand is originated from people performing…

Human mobility is subject to collective dynamics that are the outcome of numerous individual choices. Smart card data which originated as a means of facilitating automated fare collections has emerged as an invaluable source for analyzing…

Internet access is a special resource of which needs has become universal across the public whereas the service is operated in the private sector. Mobile Network Operators (MNOs) put efforts for management, planning, and optimization;…

Timings of human activities are marked by circadian clocks which in turn are entrained to different environmental signals. In an urban environment the presence of artificial lighting and various social cues tend to disrupt the natural…

For the last few years, the amount of data has significantly increased in the companies. It is the reason why data analysis methods have to evolve to meet new demands. In this article, we introduce a practical analysis of a large database…

The internet activity records (IARs) of a mobile cellular network posses significant information which can be exploited to identify the network's efficacy and the mobile users' behavior. In this work, we extract useful information from the…

Location-based social network data offers the promise of collecting the data from a large base of users over a longer span of time at negligible cost. While several studies have applied social network data to activity and mobility analysis,…

The exponential growth in mobile data demand necessitates intelligent management of telecommunications infrastructure to ensure Quality of Service (QoS) and operational efficiency. This paper presents a comprehensive analysis of a…

In transport modeling and prediction, trip purposes play an important role since mobility choices (e.g. modes, routes, departure times) are made in order to carry out specific activities. Activity based models, which have been gaining…

Traditional cellular service was designed for global connectivity, but business and logistical constraints led to its fragmentation, with deployments limited to individual countries and regions. Initiatives like Mobile Virtual Network…

Because of the complexity of urban transportation networks and the temporal changes in traffic conditions, it is difficult to assess real-time traffic situations. However, the development of information terminals has made it easier to…

Human mobility is an important characteristic of human behavior, but since tracking personalized position to high temporal and spatial resolution is difficult, most studies on human mobility patterns rely largely on mathematical models.…

Mobile phone datasets allow for the analysis of human behavior on an unprecedented scale. The social network, temporal dynamics and mobile behavior of mobile phone users have often been analyzed independently from each other using mobile…

Data volume grows explosively with the proliferation of powerful smartphones and innovative mobile applications. The ability to accurately and extensively monitor and analyze these data is necessary. Much concern in mobile data analysis is…

The rapidly increasing use of electric vehicles (EVs) has made it even more important to manage the charging infrastructure sustainably. The expansion of charging station networks, especially in large cities, creates serious logistical…

Traffic learning and prediction is at the heart of the evaluation of the performance of telecommunications networks and attracts a lot of attention in wired broadband networks. Now, benefiting from the big data in cellular networks, it…

Cellular traffic prediction is of great importance for operators to manage network resources and make decisions. Traffic is highly dynamic and influenced by many exogenous factors, which would lead to the degradation of traffic prediction…

Social network data offer interesting opportunities in urban studies. In this study, we used Twitter data to analyse city dynamics over the course of the day. Users of this social network were grouped according to city zone and time slot in…

The growing competition drives the mobile network operators (MNOs) to explore adding time flexibility to the traditional data plan, which consists of a monthly subscription fee, a data cap, and a per-unit fee for exceeding the data cap. The…