Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.13091/983
Title: ANN estimation model for photogrammetry-based UAV flight planning optimisation
Authors: Makineci, Hasan Bilgehan
Karabörk, H.
Durdu, A.
Keywords: Artificial Neural-Network
Grey Wolf Optimizer
Drone Delivery
Path
Algorithm
Connectivity
Intelligence
Design
Publisher: TAYLOR & FRANCIS LTD
Abstract: Artificial intelligence (AI) is undergoing a ground-breaking period. Recently, AI affects almost every part of human life. Using AI in path planning for Unmanned Aerial Vehicle (UAV) attracts attention as a novel need. The inputs that form the base of UAV use in photogrammetry are UAV Type (UT), Ground Sampling Distance (GSD), Overlap Rates (OR), and Atmospheric Conditions (AC). Input parameters directly impact the UAV's Flight Time (FT) and Battery Status (BS). Weighting and optimizing these parameters are the main ideas of this study. The effects of input values (GSD, OR, UT, AC) on the outputs (BS and FT) were optimized using Artificial Neural Networks (ANN) in this study. For the analysis, results have been produced in which different training algorithms are preferred (Gradient Descent - GD - and Levenberg-Marquardt - LM). The GD algorithm has reached 77.65% accuracy in FT estimation and 80.91% estimation accuracy on normalized data on the BS. Then, the correlation between the produced model and the input parameters and the output parameters was determined, and the weights of the inputs were revealed. As a result, it was determined that the AC parameter has the most significant effect on BS and FT. Also, it has been identified that the normalization process has a considerable impact on optimization.
URI: https://doi.org/10.1080/01431161.2021.1945159
https://hdl.handle.net/20.500.13091/983
ISSN: 0143-1161
1366-5901
Appears in Collections:Mühendislik ve Doğa Bilimleri Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collections
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collections

Files in This Item:
File SizeFormat 
ANN estimation model for photogrammetry based UAV flight planning optimisation.pdf
  Until 2030-01-01
5.82 MBAdobe PDFView/Open    Request a copy
Show full item record



CORE Recommender

SCOPUSTM   
Citations

1
checked on Mar 23, 2024

WEB OF SCIENCETM
Citations

5
checked on Mar 23, 2024

Page view(s)

280
checked on Mar 25, 2024

Download(s)

6
checked on Mar 25, 2024

Google ScholarTM

Check




Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.