Symbolic Regression-Based Modeling for Aerodynamic Ground-to-Flight Deviation Laws of Aerospace Vehicles
The correlation between aerodynamic data obtained from ground and flight tests is crucial in developing aerospace vehicles. This paper proposes methods for modelling this correlation that combine feature extraction and symbolic regression. The neighborhood component analysis (NCA) method is utilized...
Saved in:
| Main Authors: | Di Ding, Qing Wang, Qin Chen, Lei He |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-05-01
|
| Series: | Aerospace |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2226-4310/12/6/455 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A New Aerodynamic Domain Model (ADM) for Enhancing the Reliability of Spin Flight Vehicle Simulations
by: Shenghui Lv, et al.
Published: (2025-04-01) -
ON THE IMPACT OF FLIGHT SAFETY CERTIFICATION REQUIREMENTS ON THE AERODYNAMIC EFFICIENCY OF COMMERCIAL AIRPLANES
by: V. I. Shevyakov
Published: (2018-03-01) -
Aerodynamics: a different perspective with profound implications
by: Adam B. Suppes, et al.
Published: (2025-07-01) -
Aerodynamic and Inertial Loading Effects of Insect-Inspired Appendages in Small Unmanned Aerial Vehicles
by: Titilayo Ogunwa, et al.
Published: (2025-01-01) -
THE FORMATION OF THE CONTOUR OF THE DOCUMENTED AND REAL FLIGHT SAFETY IN THE SYSTEM OF THE INFORMATION PROVISION OF SAFETY OF FLIGHTS
by: B. I. Bachkalo, et al.
Published: (2016-11-01)