0000000000352337

AUTHOR

Mikko Perttunen

showing 1 related works from this author

Applying Wavelet Packet Decomposition and One-Class Support Vector Machine on Vehicle Acceleration Traces for Road Anomaly Detection

2013

Road condition monitoring through real-time intelligent systems has become more and more significant due to heavy road transportation. Road conditions can be roughly divided into normal and anomaly segments. The number of former should be much larger than the latter for a useable road. Based on the nature of road condition monitoring, anomaly detection is applied, especially for pothole detection in this study, using accelerometer data of a riding car. Accelerometer data were first labeled and segmented, after which features were extracted by wavelet packet decomposition. A classification model was built using one-class support vector machine. For the classifier, the data of some normal seg…

Computer sciencebusiness.industryIntelligent decision support systemPattern recognitionMachine learningcomputer.software_genreWavelet packet decompositionSupport vector machineComputerSystemsOrganization_MISCELLANEOUSAnomaly detectionVehicle accelerationArtificial intelligencebusinesscomputerClassifier (UML)
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