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


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 :Discovering Program Topoi via Hierarchical Agglomerative Clustering - 2018ABSTRACT:In long lifespan software systems, specification documents will be outdated or even missing. Developing new software releases or
PROJECT TITLE :Application of Text Classification and Clustering of Twitter Data for Business Analytics - 2018ABSTRACT:In the recent years, social networks in business are gaining unprecedented popularity as a result of of their
PROJECT TITLE :Phase Transitions and a Model Order Selection Criterion for Spectral Graph Clustering - 2018ABSTRACT:One in every of the longstanding open issues in spectral graph clustering (SGC) is the thus-called model order
PROJECT TITLE :Hierarchical Clustering Given Confidence Intervals of Metric Distances - 2018ABSTRACT:This Project considers metric the exact dissimilarities between pairs of points aren't unknown but known to belong to some interval.
PROJECT TITLE :Unified Discriminative and Coherent Semi-Supervised Subspace Clustering - 2018ABSTRACT:The ubiquitous large, complex, and high dimensional datasets in computer vision and machine learning generates the matter of

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

Project Enquiry