Spatial Information-Aware Flight Safety Forecasting Model for Unmanned Aerial Vehicles Based on Deep Learning and Grey Analysis DOI Creative Commons
Mingbo Pan, Yi‐Kai Wang, Weibin Su

et al.

IEEE Access, Journal Year: 2024, Volume and Issue: 12, P. 70729 - 70741

Published: Jan. 1, 2024

Ensuring flight safety for unmanned aerial vehicles (UAVs) is a critical concern, necessitating effective mathematical modeling forecasting in both academic and industrial contexts. This study addresses this need by combining the capabilities of deep neural networks grey analysis to create comprehensive approach focused on spatial information service (SIS). The paper introduces novel information-aware security model UAVs, emphasizing transformative impact new methodology. Traditionally, factors influencing are identified formulated based SIS chain technology, management rules, business processes, verification. To address challenges posed significant data volatility missing sample dateset, non-equally spaced GM (1,1) with an approximate non-simultaneous exponential law series developed prediction. Subsequently, multiple encoded input into specific BP network structure. concludes simulation experiments evaluate proposed model. results demonstrate that integration learning effectively recognizes risks high efficiency. underscores potential enhancing UAV forecasting.

Language: Английский

Machine Learning Applications in UAV Swarms DOI
Sadaf Hussain,

Tanweer Sohail,

Muhammad Adnan Khan

et al.

Apress eBooks, Journal Year: 2025, Volume and Issue: unknown, P. 127 - 169

Published: Jan. 1, 2025

Language: Английский

Citations

0
Optimizing multi-drone patrol path planning under uncertain flight duration: a robust model and adaptive large neighborhood search with simulated annealing DOI
Xiaoduo Li, He Luo, Guoqiang Wang

et al.

Applied Soft Computing, Journal Year: 2025, Volume and Issue: unknown, P. 113107 - 113107

Published: April 1, 2025

Language: Английский

Citations

0
Temettü Verimi ile Karlılık Oranları Arasındaki İlişki: Borsa İstanbul Temettü 25 Endeksinde Bir İnceleme DOI Creative Commons
Arif Çilek, Onur Şeyranlıoğlu

Cumhuriyet Üniversitesi İktisadi ve İdari Bilimler Dergisi, Journal Year: 2023, Volume and Issue: unknown

Published: Dec. 25, 2023

Temettü verimi hisse senedi yatırımcılarına uzun vadede düzenli ve sürekli gelir getirmesi bakımından önemli bir gösterge olduğundan, piyasalarında yatırımcılar temettü dağıtan şirketlere portföylerinde öncelik vermektedirler. Bu çalışmada, Borsa İstanbul 25 endeksinde işlem gören şirketlerin 2020-2022 döneminde ile karlılık oranları arasındaki ilişkinin belirlenmesi amaçlanmıştır. Şirketlerin sıralamalarının belirlenmesinde aktif karlılığı, esas faaliyet kar marjı, FAVÖK net özsermaye ROİC ROCE oranı değerlendirme kriteri olarak çalışmaya dâhil edilmiştir. Değerlendirme kriterleri objektif ağırlıklandırma yöntemi olan CRITIC ağırlıklandırılmıştır. Gri İlişkisel Analiz kullanılarak oranlarına göre gri ilişki dereceleri belirlenerek büyükten küçüğe doğru sıralanmıştır. Önem ağırlığı en yüksek kriter 2020 2022 yılında karlılığı olurken, 2021 ise olmuştur. önem düşük belirlenmiştir. ilişkisel derecelere şirketler EGEEN, GWIND TTRAK, TTRAK GWIND, TOASO tespit BIST GİA ölçülen sıralaması arasında yıllarında pozitif ilişki, negatif olduğu ancak bu istatistiksel anlamlı olmadığı sonucuna ulaşılmıştır.

Citations

2
Rapid trajectory generation for quadrotor with limited motor speed DOI
Shikai Shao,

Yi Guo,

Yuanjie Zhao

et al.

Proceedings of the Institution of Mechanical Engineers Part G Journal of Aerospace Engineering, Journal Year: 2024, Volume and Issue: 238(5), P. 501 - 512

Published: Feb. 12, 2024

Planning a safe and dynamic flyable trajectory for unmanned aerial vehicle (UAV) is the precondition autonomous flight. Considering environmental complexity flight safety under limited motor speed, we proposed new time-segmented planning method, which can ensure speed within allowable range achieve Firstly, candidate quadrotor UAV expressed by high-order polynomials. Herein, polynomial used as expression of trajectory, nonlinear programming (NLP) to calculate coefficient. Then, two strategies an initial value calculation method are improve efficiency NLP. Furthermore, aiming at problem that cannot meet current limit constraint after drops, adjustment strategy based on feasible designed. The presented in this paper not only enhances flexibility process, improves solving algorithm but also enables continue flying when limited. Finally, simulation analysis comparison illustrate effectiveness superiority method.

Language: Английский

Citations

0
Spatial Information-Aware Flight Safety Forecasting Model for Unmanned Aerial Vehicles Based on Deep Learning and Grey Analysis DOI Creative Commons
Mingbo Pan, Yi‐Kai Wang, Weibin Su

et al.

IEEE Access, Journal Year: 2024, Volume and Issue: 12, P. 70729 - 70741

Published: Jan. 1, 2024

Ensuring flight safety for unmanned aerial vehicles (UAVs) is a critical concern, necessitating effective mathematical modeling forecasting in both academic and industrial contexts. This study addresses this need by combining the capabilities of deep neural networks grey analysis to create comprehensive approach focused on spatial information service (SIS). The paper introduces novel information-aware security model UAVs, emphasizing transformative impact new methodology. Traditionally, factors influencing are identified formulated based SIS chain technology, management rules, business processes, verification. To address challenges posed significant data volatility missing sample dateset, non-equally spaced GM (1,1) with an approximate non-simultaneous exponential law series developed prediction. Subsequently, multiple encoded input into specific BP network structure. concludes simulation experiments evaluate proposed model. results demonstrate that integration learning effectively recognizes risks high efficiency. underscores potential enhancing UAV forecasting.

Language: Английский

Citations

0