PROJECT TITLE :

Clustering Weekly Patterns of Human Mobility Through Mobile Phone Data - 2018

ABSTRACT:

With the fast growth of mobile phone networks during the last decades, decision detail records (CDR) are used as approximate indicators for giant scale studies on human and concrete mobility. Although coarse and limited, CDR are a real marker of human presence. During this Project, we tend to use more than 80zero million CDR to identify weekly patterns of human mobility through itinerant data. Our methodology is predicated on the classification of individuals into six distinct presence profiles where we tend to focus on the inherent temporal and geographical characteristics of each profile among a territory. Then, we have a tendency to use an occurrence-based mostly algorithm to cluster people and we establish twelve weekly patterns. We tend to leverage these results to analyze population estimates adjustment processes and thus, we propose new indicators to characterize the dynamics of a territory. Our model has been applied to real information coming back from more than one.half-dozen million individuals and demonstrates its relevance. The product of our work can be used by native authorities for human mobility analysis and urban designing.


Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here


PROJECT TITLE : Multi-View Clustering with the Cooperation of Visible and Hidden Views ABSTRACT: The use of multi-view data in real-world applications is becoming increasingly common, and as a result, numerous multi-view clustering
PROJECT TITLE : SCHAIN-IRAM: An Efficient and Effective Semi-Supervised Clustering Algorithm for Attributed Heterogeneous Information Networks ABSTRACT: A heterogeneous information network, also known as an HIN, is a network in
PROJECT TITLE : RDMN: A Relative Density Measure Based on MST Neighborhood for Clustering Multi-Scale Datasets ABSTRACT: Techniques for discovering intrinsic clusters that are based on density do so by classifying the regions
PROJECT TITLE : Fully Dynamic kk-Center Clustering With Improved Memory Efficiency ABSTRACT: Any machine learning library worth its salt will include both static and dynamic clustering algorithms as core components. The sliding
PROJECT TITLE : ESA-Stream: Efficient Self-Adaptive Online Data Stream Clustering ABSTRACT: A wide variety of big data applications generate an enormous amount of streaming data that is high-dimensional, real-time, and constantly

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry