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PAVEMENT STRUCTURE EVALUATION WITH MACHINE LEARNING FOCUSING SHAPE OF CRACK AND RUTS ON SURFACE
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- WATANABE Sinichi
- (国研)土木研究所 道路技術研究グループ
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- MAEKAWA Ryota
- (国研)土木研究所 道路技術研究グループ
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- NAGATSUKA Tatsuya
- (国研)土木研究所 道路技術研究グループ
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- YABU Masayuki
- (国研)土木研究所 道路技術研究グループ
Bibliographic Information
- Other Title
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- ひび割れとわだち掘れの形状に着目した舗装構造評価への機械学習の適用
Description
<p> The technical standard for pavement inspection in Japan attaches importance to structural soundness of subbase layer and below. The authors have built a new way to evaluate structural soundness without traffic restrictions. This evalutation way uses crack shape, rut shape, and machine learning method (convolutional neural network:CNN). Deflection D0 was estimated using the crack diagram, cross-sectional profile and asphalt layer thickness. This evaluation way estimated the deflection D0 with higher accuracy than the conventional method using cracking ratio and rut depth.</p>
Journal
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- Journal of Japan Society of Civil Engineers, Ser. E1 (Pavement Engineering)
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Journal of Japan Society of Civil Engineers, Ser. E1 (Pavement Engineering) 76 (2), I_11-I_19, 2020
Japan Society of Civil Engineers
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Details 詳細情報について
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- CRID
- 1391131406311421696
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- NII Article ID
- 130007980617
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- ISSN
- 21856559
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- Text Lang
- ja
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- Data Source
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- JaLC
- Crossref
- CiNii Articles
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- Abstract License Flag
- Disallowed