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dc.contributor.authorLow, Xian Haoen_US
dc.identifier.citationLow, X. H. (2022). Application of machine learning techniques in vehicle collision detection. Final Year Project (FYP), Nanyang Technological University, Singapore.
dc.description.abstractVehicle accidents are still happening daily even with the existing technological support provided. This can be due to limitations of the technology and/or human error. Using a newer technology, the vehicle-to-everything communication, the aim is to use machine learning techniques to make predictions on GPS data, in order to provide an early collision warning system. With such a system in place, drivers would be alerted if a collision might happen several seconds prior and be mentally prepared for the potential threat. The algorithms explored in this study is the multi-layered perceptron classifier, random forest and Tabnet.en_US
dc.publisherNanyang Technological Universityen_US
dc.subjectEngineering::Computer science and engineering::Computing methodologies::Artificial intelligenceen_US
dc.titleApplication of machine learning techniques in vehicle collision detectionen_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorGuan Yong Liangen_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeBachelor of Engineering (Information Engineering and Media)en_US
dc.contributor.researchContinental-NTU Corporate Lab in RTPen_US
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Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)
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