インフラレジリエンスのためのマルチモーダルAIフュージョン:SDG-9に準拠したリアルタイム都市分析フレームワーク
N S Kalyan Chakravarthi1, S Jafar Ali Ibrahim1, Raenu Kolandaisamy1
1Institute of Computer Science and Digital Innovation, UCSI University, 1 Jalan UCSI, UCSI Heights (Taman Connaught), Cheras, Kuala Lumpur, Malaysia.
Frontiers in artificial intelligence
|February 25, 2026
まとめ
この研究では、都市洪水リスク管理を強化するためのLong-Short Term Memory(LSTM)とGraph Neural Networks(GNN)を使用した新しいAIフレームワークを紹介します。ハイブリッドモデルは、従来のモデルを上回るレジリエンススコアリングと意思決定を改善します。
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