On Learning Fuel Consumption Prediction in Vehicle Clusters

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

Identifying granular patterns of differentiation and learning predictors of product performance are key drivers to capitalize on competitive market segments. In this paper, we propose an approach to identify granular product patterns by using Hierarchical Clustering, and to learn predictors of product performance from historical data by using Genetic Programming. Computational experiments using more than twenty thousand vehicle models collected over the last thirty years shows (1) the feasibility to identify vehicle differentiation at different levels of granularity by hierarchical clustering, and (2) the good predictive ability of learned fuel consumption predictors in vehicle cluster. We believe our approach introduces the building blocks to further advance on studies regarding product differentiation and market segmentation by using data-intensive approaches.

本文言語English
ホスト出版物のタイトルProceedings - 2018 IEEE 42nd Annual Computer Software and Applications Conference, COMPSAC 2018
編集者Claudio Demartini, Sorel Reisman, Ling Liu, Edmundo Tovar, Hiroki Takakura, Ji-Jiang Yang, Chung-Horng Lung, Sheikh Iqbal Ahamed, Kamrul Hasan, Thomas Conte, Motonori Nakamura, Zhiyong Zhang, Toyokazu Akiyama, William Claycomb, Stelvio Cimato
出版社IEEE Computer Society
ページ116-121
ページ数6
ISBN(電子版)9781538626665
DOI
出版ステータスPublished - 2018 6 8
イベント42nd IEEE Computer Software and Applications Conference, COMPSAC 2018 - Tokyo, Japan
継続期間: 2018 7 232018 7 27

出版物シリーズ

名前Proceedings - International Computer Software and Applications Conference
2
ISSN(印刷版)0730-3157

Other

Other42nd IEEE Computer Software and Applications Conference, COMPSAC 2018
CountryJapan
CityTokyo
Period18/7/2318/7/27

ASJC Scopus subject areas

  • Software
  • Computer Science Applications

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