Modeling and Prediction of Jet Aircraft Flight Dynamics Using Machine Learning and Advanced Computational Simulations

This paper presents a model for predicting the flight dynamics of jet aircraft using Machine Learning (ML) techniques and advanced computational simulations. The objective of this paper is to explore the potential of ML algorithms in simulating the dynamic behavior of jet aircraft and evaluating their performance under various flight conditions. Initially, experimental and simulated flight data are collected and processed using ML algorithms such as Artificial Neural Networks (ANN) and Support Vector Machines (SVM). The simulation results demonstrate that the proposed methods can achieve high accuracy in predicting aircraft behavior and flight dynamics in various conditions, including environmental variations and system failures. Ultimately, this research provides insights into enhancing flight simulation models and their application in the design and control of jet aircraft operations.

کلیدواژه ها:

Flight Dynamics ، Machine Learning ، Jet Aircraft ، Neural Networks ، Support Vector Machines ، Computational Fluid Dynamics (CFD)