書誌事項
- タイトル別名
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- PROPOSAL OF A CLASSIFICATION METHOD FOR PUBLIC SPACE USAGE BASED ON PEDESTRIAN TRAJECTORY DATA
抄録
<p>Herein, we propose a machine learning method based on pedestrian trajectory data to classify public space usage states and discriminate unknown usage states. Aggregated feature values for each small cell were regarded as feature vectors representing the usage state. They were classified into usage state “types” via principal component analysis and x-means clustering. During validation using actual data, 16 types appearing at specific times and days were identified, and 1.1% of the test data were determined to be “new usage states” not found in the training data. This method helps understand long-term and complex variations in public space utilization patterns.</p>
収録刊行物
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- 日本建築学会計画系論文集
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日本建築学会計画系論文集 87 (792), 476-486, 2022-02-01
日本建築学会
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詳細情報 詳細情報について
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- CRID
- 1390009454815671040
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- NII論文ID
- 130008150343
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- ISSN
- 18818161
- 13404210
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- 本文言語コード
- ja
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- データソース種別
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- JaLC
- Crossref
- CiNii Articles
- KAKEN
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- 抄録ライセンスフラグ
- 使用不可