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Abstract
In this paper we propose a Neural Knowledge DNA based framework that is capable of learning from the car’s daily operation. The Neural Knowledge 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 behaviour. The experimental data is collected via smart-phone sensors. The initial results are presented and the direction for our future research is defined.
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Authors (6)
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Haoxi Zhang
- Chengdu University Computer Science
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Fei Li
- Chengdu University Computer Science
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Juan Wang
- Chengdu University Computer Science
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Lei Shi
- Chengdu University Computer Science
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Cesar Sanín
- Newcastle University Mechanical Engineering
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- Publication version
- Accepted or Published Version
- DOI:
- Digital Object Identifier (open in new tab) 10.1080/01969722.2016.1276780
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Details
- Category:
- Articles
- Type:
- artykuł w czasopiśmie wyróżnionym w JCR
- Published in:
-
CYBERNETICS AND SYSTEMS
no. 48,
edition 3,
pages 267 - 273,
ISSN: 0196-9722 - Language:
- English
- Publication year:
- 2017
- Bibliographic description:
- Zhang H., Li F., Wang J., Shi L., Sanín C., Szczerbicki E.: Adding Intelligence to Cars Using the Neural Knowledge DNA// CYBERNETICS AND SYSTEMS. -Vol. 48, iss. 3 (2017), s.267-273
- DOI:
- Digital Object Identifier (open in new tab) 10.1080/01969722.2016.1276780
- Verified by:
- Gdańsk University of Technology
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