@techreport{oai:ipsj.ixsq.nii.ac.jp:00232603,
 author = {青木, 泰浩 and 間嶋, 義喜 and 鈴木, 美彦 and Yasuhiro, Aoki and Yoshiki, Mashima and Yoshihiko, Suzuki},
 issue = {43},
 month = {Feb},
 note = {スマートフォンの普及により，人々の詳細な移動履歴を知ることが可能となり，位置情報データを用いた人流予測・人流分析が盛んに行われている．短期の定常的な人流予測は，過去の事例から，精度良く実現されていることがわかる．しかし，人々の行動指針は，イベント・天候・季節など外部条件により動的に変化し，それに伴い混雑状況も大きく変化することから，人流を客観的に把握・分析する技術が必要となる．そこで，本研究では，ポイント型人流データと POI データを統合し，都市部の人流をマクロに分析・評価する方法を提案する．, With the spread of smartphones, it has become possible to know people's movement history in detail, and people flow prediction and analysis using location information data is actively being carried out. In people flow prediction, short-term steady predictions are achieved with high accuracy by learning past cases. However, because urban functions and people's behavioral guidelines change dynamically, the congestion situation changes greatly depending on various events and other conditions. For this reason, we believe that it is necessary to objectively understand and analyze people's movement, and in this study, we propose a method to integrate point-type people flow data and POI data to analyze and evaluate people's movement in cities on a macro level.},
 title = {複数種類データ統合に基づく駅近郊の人流分析手法の提案},
 year = {2024}
}