On Learning Fuel Consumption Prediction in Vehicle Clusters
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- @InProceedings{Parque:2018:COMPSAC,
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author = "Victor Parque and Tomoyuki Miyashita",
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booktitle = "2018 IEEE 42nd Annual Computer Software and
Applications Conference (COMPSAC)",
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title = "On Learning Fuel Consumption Prediction in Vehicle
Clusters",
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year = "2018",
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volume = "02",
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pages = "116--121",
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abstract = "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.",
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keywords = "genetic algorithms, genetic programming",
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DOI = "doi:10.1109/COMPSAC.2018.10214",
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ISSN = "0730-3157",
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month = jul,
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notes = "Also known as \cite{8377841}",
- }
Genetic Programming entries for
Victor Parque
Tomoyuki Miyashita
Citations