Recent advances in harris hawks optimization: A comparative study and applications
The Harris hawk optimizer is a recent population-based metaheuristics algorithm that
simulates the hunting behavior of hawks. This swarm-based optimizer performs the …
simulates the hunting behavior of hawks. This swarm-based optimizer performs the …
A comprehensive survey on aquila optimizer
Aquila Optimizer (AO) is a well-known nature-inspired optimization algorithm (NIOA) that
was created in 2021 based on the prey grabbing behavior of Aquila. AO is a population …
was created in 2021 based on the prey grabbing behavior of Aquila. AO is a population …
Intrusion detection system for IoT based on deep learning and modified reptile search algorithm
This study proposes a novel framework to improve intrusion detection system (IDS)
performance based on the data collected from the Internet of things (IoT) environments. The …
performance based on the data collected from the Internet of things (IoT) environments. The …
Wireless communications for data security: Efficiency assessment of cybersecurity industry—A promising application for UAVs
CN Wang, FC Yang, NTM Vo, VTT Nguyen - Drones, 2022 - mdpi.com
The design of cooperative applications combining several unmanned aerial and aquatic
vehicles is now possible thanks to the considerable advancements in wireless …
vehicles is now possible thanks to the considerable advancements in wireless …
[HTML][HTML] Injection attack detection using machine learning for smart IoT applications
Smart cities are a rapidly growing IoT application. These smart cities mainly rely on wireless
sensors to connect their different components (smart devices) together. Smart cities rely on …
sensors to connect their different components (smart devices) together. Smart cities rely on …
A novel hybrid chaotic Aquila optimization algorithm with simulated annealing for unmanned aerial vehicles path planning
A Ait-Saadi, Y Meraihi, A Soukane… - Computers and …, 2022 - Elsevier
Abstract Unmanned Aerial Vehicles path planning is one of the critical issues in terms of
guaranteeing good performance in real-world applications. Basically, it is responsible for …
guaranteeing good performance in real-world applications. Basically, it is responsible for …
Predicting CO2 trapping in deep saline aquifers using optimized long short-term memory
A sustainable environment by decreasing fossil fuel utilization and anthropogenic
greenhouse gases is a globally main goal due to climate change and serious air pollution …
greenhouse gases is a globally main goal due to climate change and serious air pollution …
[HTML][HTML] Proposed algorithm for smart grid DDoS detection based on deep learning
SY Diaba, M Elmusrati - Neural Networks, 2023 - Elsevier
Abstract The Smart Grid's objective is to increase the electric grid's dependability, security,
and efficiency through extensive digital information and control technology deployment. As a …
and efficiency through extensive digital information and control technology deployment. As a …
A new intrusion detection system based on Moth–Flame Optimizer algorithm
This study relies on using a Moth–Flame Optimization (MFO) method as a search algorithm
and a Decision Tree (DT) as an evaluation algorithm to generate an efficient feature subset …
and a Decision Tree (DT) as an evaluation algorithm to generate an efficient feature subset …
Enhancing intrusion detection systems for IoT and cloud environments using a growth optimizer algorithm and conventional neural networks
Intrusion detection systems (IDS) play a crucial role in securing networks and identifying
malicious activity. This is a critical problem in cyber security. In recent years, metaheuristic …
malicious activity. This is a critical problem in cyber security. In recent years, metaheuristic …