Cutting-edge flight route prediction system for harnessing synergistic power of convolutional neural network (CNN) and K-nearest neighbors (KNN) algorithms used in aircraft, which revolutionizes aviation navigation with adaptive intelligence
	MOHANAPRIYA M; MANOJKUMAR P; KIRUTHICKRAJAN K S; JAYAVARMAN D; ILAKIYA S R S
	2024-06-18
专利权人	MOHANAPRIYA M (MOHA-Individual)
申请日期	2024-06-18
专利号	IN202441046743-A
成果简介	NOVELTY - The system revolutionizes aviation navigation with adaptive intelligence. The sophisticated utilization of CNN for precise satellite image classification enables in-depth analysis of environmental factors and potential hazards to ensure optimal flight paths. The seamless transition between CNN and KNN algorithms offers dynamic response to realtime operational variables, and provides alternative routes to optimize fuel efficiency and minimize contrail formation. The unprecedented aviation safety enhancement through CNN deep learning capabilities allows real-time identification of hazardous conditions and suboptimal flight routes. The strategic optimization of flight routes to mitigate environmental impact leverages historical data and current environmental conditions for informed decision-making. The rigorous training and validation of CNN model to accurately detect contrails amidst complex atmospheric conditions enables proactive identification and avoidance strategies. USE - Cutting-edge flight route prediction system for harnessing synergistic power of convolutional neural network (CNN) and K-nearest neighbors (KNN) algorithms used in aircraft ADVANTAGE - The flight route prediction system integrates advanced technologies to optimize aviation safety and efficiency. The iterative refinement process leveraging historical flight data continuously improves the accuracy and effectiveness of route predictions and ensures optimal performance in diverse operational scenarios. The forward-thinking approach combining advanced machine learning techniques with real world aviation challenges drives innovation in flight route planning and environmental sustainability. DESCRIPTION OF DRAWING(S) - The drawing shows a flow diagram of the cutting-edge flight route prediction system for harnessing synergistic power of CNN and KNN algorithms used in aircraft.
IPC 分类号	A01G-015/00 ; A61F-007/00 ; C10L-001/18 ; F01D-025/30 ; G01W-001/08
国家	印度
专业领域	农业科学
语种	英语
成果类型	专利
文献类型	科技成果
条目标识符	http://119.78.100.226:8889/handle/3KE4DYBR/16197
专题	中国科学院新疆生态与地理研究所
作者单位	MOHANAPRIYA M (MOHA-Individual)
推荐引用方式 GB/T 7714	MOHANAPRIYA M,MANOJKUMAR P,KIRUTHICKRAJAN K S,et al. Cutting-edge flight route prediction system for harnessing synergistic power of convolutional neural network (CNN) and K-nearest neighbors (KNN) algorithms used in aircraft, which revolutionizes aviation navigation with adaptive intelligence. IN202441046743-A[P]. 2024.

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