Applying Machine Learning Techniques to Transportation Mode Recognition Using Mobile Phone Sensor Data

IEEE Transactions on Intelligent Transportation Systems

Volumn 16, Issue 5, 2015, Pages 2406-2417

  Jahangiri, Arash ^a   Rakha, Hesham A ^a  

^a VIRGINIA TECH TRANSPORTATION INSTITUTE   (United States)

Author keywords

Cellular phone sensor data; machine learning algorithms; transportation mode recognition

Indexed keywords

ARTIFICIAL INTELLIGENCE; DECISION TREES; E-LEARNING; NEAREST NEIGHBOR SEARCH; SIGNAL ENCODING; SIMULATED ANNEALING; SMARTPHONES; SUPPORT VECTOR MACHINES; TRANSPORTATION;

K FOLD CROSS VALIDATIONS; MACHINE LEARNING TECHNIQUES; MINIMUM REDUNDANCY-MAXIMUM RELEVANCES; MULTI-CLASS CLASSIFIER; RANDOM FOREST METHODS; SIMULATED ANNEALING ALGORITHMS; SUPERVISED LEARNING METHODS; SUPPORT VECTOR MACHINE (SVMS);

LEARNING SYSTEMS;

EID: 84959525056     PISSN: 15249050     EISSN: None     Source Type: Journal    
DOI: 10.1109/TITS.2015.2405759     Document Type: Article

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