Crash Performance Prediction and Knowledge Discovery from Crash Simulation Using Data Mining
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- Ono Masamoto
- 日産自動車㈱
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- Kageyama Yusuke
- 日産自動車㈱
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- Iyama Jun
- 日産自動車㈱
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- Hara Satoshi
- 日本アイ・ビー・エム㈱
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- Rudy Raymond
- 日本アイ・ビー・エム㈱
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- Ide Tsuyoshi
- 日本アイ・ビー・エム㈱
Bibliographic Information
- Other Title
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- 衝突シミュレーションのデータマイニングによる 衝突性能予測と知識発見
- ショウトツ シミュレーション ノ データマイニング ニ ヨル ショウトツ セイノウ ヨソク ト チシキ ハッケン
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Abstract
The extensive use of computer-aided design (CAE) is a standard approach in car crash simulation. As high-performance computation gets more available at a reasonable cost, it is becoming possible to produce huge amount of intermediate data such as the displacement of individual nodes. However, little is known about how to extract useful insights from the intermediate data. This paper proposes a data mining approach to CAE-based crash simulation. Using a dimensionality reduction technique, we demonstrate that the proposed method can automatically extract useful features from the data.
Journal
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- Transactions of Society of Automotive Engineers of Japan
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Transactions of Society of Automotive Engineers of Japan 47 (4), 913-918, 2016
Society of Automotive Engineers of Japan
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Keywords
Details 詳細情報について
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- CRID
- 1390001204613376640
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- NII Article ID
- 130006321584
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- NII Book ID
- AN00105913
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- ISSN
- 18830811
- 02878321
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- NDL BIB ID
- 027580214
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- Text Lang
- ja
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- Data Source
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- JaLC
- NDL
- CiNii Articles
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- Abstract License Flag
- Disallowed