Work

Cell Phone Mobility Classification based on k-Clustering and Linear Classification

Year: 2013

Type: conference-paper

Abstract: Road traffic data is an essential element of the intelligent transportation system. However, available traffic data is insufficient to meet the current needs due to the high investment of infrastructure and traffic sensors. Therefore, obtain the traffic data from cell phone information becomes an attractive option for its widely used, high opacity and low cost. In order to get the satisfying results, the large sample sizes are necessary for existing classification algorithms, which leads to the low real-time performance and high complexity. To overcome these problems, a mobility of cell phone classification method based on k- clustering and linear classification has been proposed in this paper. The experimental results demonstrate the higher stability and accuracy of proposed method.

Source: Procedia - Social and Behavioral Sciences

DOI: 10.1016/j.sbspro.2013.08.297

Authors: Hua Wang, Shen Zhang, Xin Liu, Wei Quan

Institution: Harbin Institute of Technology

Language: English

Topic: Human Mobility and Location-Based Analysis

Subfield: Transportation

Field: Social Sciences

Domain: Social Sciences

SDGs: Industry, innovation and infrastructure, Sustainable cities and communities

Open Access status: diamond

Funders: National Science Foundation, Natural Science Foundation of Heilongjiang Province