APPLICATION OF GRAPH NEURAL NETWORKS IN OPTIMIZING FLIGHT TIME FOR THE HO CHI MINH - HANOI ROUTE=APPLICATION OF GRAPH NEURAL NETWORKS IN OPTIMIZING FLIGHT TIME FOR THE HO CHI MINH - HANOI ROUTE

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Tác giả: Ngoc Thanh Tai Le, Anh Tuan Nguyen, Hoang Hai Ngan Nguyen, Ngoc Hoang Quan Nguyen, Truong Huy Pham, Gia Bao Tran, Thi My Duyen Tran

Ngôn ngữ: eng

Ký hiệu phân loại:

Thông tin xuất bản: Tạp chí Khoa học Công nghệ Hàng Không, 2024

Mô tả vật lý: tr.2025-01-09

Bộ sưu tập: Metadata

ID: 245580

The aviation market worldwide, and in Vietnam in particular, is recovering and developing strongly after the COVID-19 pandemic. To find solutions to reduce air traffic on current ATS routes and discover new, more optimal routes to shorten flight times for aircraft flying from Ho Chi Minh to Hanoi, an optimization model has been built by applying the Graph Neural Network (GNN) model. The research team applied the Graph Neural Network (GNN) model to a specific case that could impact current ATS routes when the PLK (Pleiku) waypoint is unavailable, which may affect the current ATS route. We selected key influencing factors and calculated the shortest and most optimal new route. The application of the GNN model to solutions in the aviation industry is expected to experience significant growth and become more practical in the future, contributing to improving efficiency and operation capacity in the aviation industryThe aviation market worldwide, and in Vietnam in particular, is recovering and developing strongly after the COVID-19 pandemic. To find solutions to reduce air traffic on current ATS routes and discover new, more optimal routes to shorten flight times for aircraft flying from Ho Chi Minh to Hanoi, an optimization model has been built by applying the Graph Neural Network (GNN) model. The research team applied the Graph Neural Network (GNN) model to a specific case that could impact current ATS routes when the PLK (Pleiku) waypoint is unavailable, which may affect the current ATS route. We selected key influencing factors and calculated the shortest and most optimal new route. The application of the GNN model to solutions in the aviation industry is expected to experience significant growth and become more practical in the future, contributing to improving efficiency and operation capacity in the aviation industry
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