| アイテムタイプ |
学術雑誌論文 / Journal Article.(1) |
| 公開日 |
2023-10-06 |
| 書誌情報 |
en : Journal of Transport Geography
巻 78,
p. 70-86,
ページ数 17,
発行日 2019
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| タイトル |
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|
タイトル |
Determination of the influence factors on household vehicle ownership patterns in Phnom Penh using statistical and machine learning methods |
|
言語 |
en |
| 言語 |
|
|
言語 |
eng |
| キーワード |
|
|
言語 |
en |
|
主題Scheme |
Other |
|
主題 |
Vehicle ownership |
| キーワード |
|
|
言語 |
en |
|
主題Scheme |
Other |
|
主題 |
Phnom Penh |
| キーワード |
|
|
言語 |
en |
|
主題Scheme |
Other |
|
主題 |
Features ranking |
| キーワード |
|
|
言語 |
en |
|
主題Scheme |
Other |
|
主題 |
Multinomial logit model |
| キーワード |
|
|
言語 |
en |
|
主題Scheme |
Other |
|
主題 |
Neural networks |
| キーワード |
|
|
言語 |
en |
|
主題Scheme |
Other |
|
主題 |
Random forests |
| 資源タイプ |
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|
資源タイプ識別子 |
http://purl.org/coar/resource_type/c_6501 |
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資源タイプ |
journal article |
| アクセス権 |
|
|
アクセス権 |
open access |
|
アクセス権URI |
http://purl.org/coar/access_right/c_abf2 |
| 著者 |
Ha, Tran Vinh
浅田, 拓海
有村, 幹治
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| 抄録 |
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内容記述タイプ |
Abstract |
|
内容記述 |
Vehicle ownership patterns and their determinants play an important role in transportation policy-making. This issue has been paid even greater attention in developing countries that aspire to reach sustainable transportation development goals in the era of urbanization and globalization. In this study, the multinomial logit model, neural networks and random forest were applied to examine the features' impact level and to also predict vehicle ownership patterns in Phnom Penh city. The empirical results indicate that household income is the most powerful variable affecting motorization in Phnom Penh. Supplementation of individual trip characteristics such as total number of trips made, number of trips made for work purposes and overall travel distance all make effective contributions as classifiers. Furthermore, it is acknowledged that the machine-learning approach outperformed not only in terms of predicting accuracy, but also in dealing with unbalanced categories when compared with the statistical approach. This detection supplies the advantages of applying machine learning techniques in terms of, but not limited to, the field of vehicle ownership. |
|
言語 |
en |
| 出版者 |
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|
出版者 |
Elsevier |
|
言語 |
en |
| 出版者版へのリンク |
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|
言語 |
ja |
|
表示名 |
10.1016/j.jtrangeo.2019.05.015 |
|
URL |
https://doi.org/10.1016/j.jtrangeo.2019.05.015 |
| DOI |
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関連タイプ |
isIdenticalTo |
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|
識別子タイプ |
DOI |
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|
関連識別子 |
10.1016/j.jtrangeo.2019.05.015 |
| ISSN |
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収録物識別子タイプ |
PISSN |
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収録物識別子 |
09666923 |
| 権利 |
|
|
権利情報 |
© 2019 The Authors. Published by Elsevier Ltd. |
|
言語 |
en |
| 著者版フラグ |
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|
出版タイプ |
VoR |
|
出版タイプResource |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
1-s2.0-S096669231830886X-main.pdf (4.6 MB)
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