Research on Flight Data Mining and Analysis Algorithms Based on Intelligent Cockpit

This article explores the integration application of intelligent cockpit technology with flight DM (Data Mining) and analysis algorithms. The main purpose of the research is to develop algorithms that can improve flight safety, optimize performance, and provide decision support to meet the needs of the aviation industry. In terms of methodology, we adopted data science and machine learning methods to preprocess, feature engineering, and model development large-scale flight data. The experimental results show that the research results indicate that the altitude obtained from cluster analysis is maintained between 20000 and 30000 feet in cruise altitude testing, while the altitude tested by the algorithm in this paper is maintained between 30000 and 40000 feet. This altitude range has multiple advantages, including less air resistance, higher fuel efficiency, and better cruising performance. Our algorithm has also optimized flight performance, including improved fuel efficiency and range optimization. In summary, this study provides strong methods and experimental support for the integration application of intelligent cockpit technology and flight DM, and provides important references and inspirations for future research and development.