@inproceedings{50ae5852031643a58374b00b23a14b1a,
title = "Estimating instrumentation data acquired during flight test of a helicopter using predictor models",
abstract = "In this paper, we propose a hybrid system consisting of decision trees and neural networks to calculate the measurement faults of sensor readings and to predict the actual values in a flight test of a helicopter in production. We present the architecture of the models, and extensive test results.",
keywords = "Data confidence, Data prediction, Flight test, Helicopter, Instrumentation",
author = "Baris Coskun and Burkay Genc",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 19th IEEE International Conference on Smart Technologies, EUROCON 2021 ; Conference date: 06-07-2021 Through 08-07-2021",
year = "2021",
month = jul,
day = "6",
doi = "10.1109/EUROCON52738.2021.9535625",
language = "English",
series = "EUROCON 2021 - 19th IEEE International Conference on Smart Technologies, Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "164--169",
editor = "Mariya Antyufeyeva",
booktitle = "EUROCON 2021 - 19th IEEE International Conference on Smart Technologies, Proceedings",
address = "United States",
}