Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/61857
Title: Adding Intelligence to Cars Using the Neural Knowledge DNA
Contributor(s): Zhang, Haoxi (author); Li, Fei (author); Wang, Juan (author); Wang, Zuli (author); Shi, Lei (author); Zhao, Jun (author); Sanin, Cesar  (author)orcid ; Szczerbicki, Edward (author)
Publication Date: 2017
Early Online Version: 2017-03-02
DOI: 10.1080/01969722.2016.1276780
Handle Link: https://hdl.handle.net/1959.11/61857
Abstract: 

In this paper, we propose a Neural Knowledge DNA (NK-DNA)-based framework that is capable of learning from the car’s daily operations and reusing such learned knowledge in future tasks. The NK-DNA is a novel knowledge representation and reasoning approach designed to support discovering, storing, reusing, improving, and sharing knowledge among machines and computing devices. We examine our framework for drivers’ classification based on their driving behaviors. The experimental data are collected via smartphone sensors. The initial results are presented, and the direction for our future research is defined.

Publication Type: Journal Article
Source of Publication: Cybernetics and Systems, 48(3), p. 267-273
Publisher: Taylor & Francis Inc
Place of Publication: United States of America
ISSN: 1087-6553
0196-9722
Fields of Research (FoR) 2020: 4602 Artificial intelligence
Peer Reviewed: Yes
HERDC Category Description: C1 Refereed Article in a Scholarly Journal
Appears in Collections:Journal Article
School of Science and Technology

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