Machine Learning and Deep Learning for Intelligent Systems in Small Aircraft Applications-Reference-Cited by-同舟云学术

Machine Learning and Deep Learning for Intelligent Systems in Small Aircraft Applications

Published:2023-11-27 Issue: Volume: Page:251-275
ISSN:2327-0411
Container-title:Handbook of Research on AI and ML for Intelligent Machines and Systems
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Author:

Rahamathunnisa U.¹,Mohanty Akash²,Sudhakar K.³,Anitha Jebamani S.⁴,Udendhran R.⁵,Myilsamy Sureshkumar⁶

Affiliation:

1. School of Computer Science Engineering and Information Systems, Vellore Institute of Technology, India

2. School of Mechanical Engineering, Vellore Institute of Technology, India

3. Department of Computer Science and Engineering, Madanapalle Institute of Technology and Science, Madanapalle, India

4. Department of Information Technology, Sri Sai Ram Engineering College, Chennai, India

5. Department of Computational Intelligence, SRM Institute of Science and Technology, India

6. Mechanical Engineering, Bannari Amman Institute of Technology, India

Abstract

This chapter explores the integration of machine learning and deep learning techniques in small aircraft applications. The aviation industry is exploring innovative solutions to improve safety, efficiency, and performance in these operations. The chapter explores the advantages, challenges, and future prospects of implementing intelligent systems in small aircraft, including autopilot systems, navigation assistance, fault detection, and pilot support systems. Real-world case studies and applications demonstrate the transformative impact of these technologies on small aircraft operations. The chapter provides a comprehensive overview of the latest advancements in machine learning and deep learning, highlighting their pivotal role in improving small aircraft intelligence, safety, and efficiency.

Publisher

IGI Global

Reference55 articles.

1. Smart Precision Agriculture Using IoT and WSN

2. Digital Education System During the COVID-19 Pandemic

3. Intelligent Systems in aerospace

4. Scientific use of Game Engines for Flight Simulation and Human Machine Interface Development.;J.Ament;CEAS Aeronautical Journal,2023

5. Anitha, C., Komala, C., Vivekanand, C. V., Lalitha, S., & Boopathi, S. (2023). Artificial Intelligence driven security model for Internet of Medical Things (IoMT). IEEE Explore, 1–7.