Classification of Cellular Phone Mobility using Naive Bayes Model

摘要: Road traffic data is a fundamental element of the intelligent system (ITS). However, availability road currently limited due to high investment sensors and associated infrastructure. Using cellular phone information as becomes an attractive alternative because its low cost, widespread networks, large number phones potential probes. in practice, collected consists various types mobility, either related or unrelated traffic. In this paper, we proposed method classify two i.e., sky train pedestrian, from information. Two key attributes, 1) unique cell ID 2) average dwell time are used Navies Bayes classification model. The experimental results show promising performance with accuracy up 93.1%. This suggests use data.