Machine learning optimization techniques: a Survey, classification, challenges, and Future Research Issues
K Bian, R Priyadarshi - Archives of Computational Methods in Engineering, 2024 - Springer
Optimization approaches in machine learning (ML) are essential for training models to
obtain high performance across numerous domains. The article provides a comprehensive …
obtain high performance across numerous domains. The article provides a comprehensive …
Federated Learning for Computational Offloading and Resource Management of Vehicular Edge Computing in 6G-V2X Network
The Sixth Generation network (6G) can support autonomous driving along with various
vehicular applications like Vehicular Edge Computing (VEC), a distributed computing …
vehicular applications like Vehicular Edge Computing (VEC), a distributed computing …
Overtaking Mechanisms Based on Augmented Intelligence for Autonomous Driving: Datasets, Methods, and Challenges
V Chamola, A Chougule, A Sam… - IEEE Internet of …, 2024 - ieeexplore.ieee.org
The field of autonomous driving research has made significant strides towards achieving full
automation, endowing vehicles with self-awareness and independent decision-making …
automation, endowing vehicles with self-awareness and independent decision-making …
Adaptive Swarm Intelligent Offloading Based on Digital Twin-assisted Prediction in VEC
Vehicular Edge Computing (VEC) is the transportation version of Mobile Edge Computing
(MEC). In VEC, task offloading enables vehicles to offload computing tasks to nearby …
(MEC). In VEC, task offloading enables vehicles to offload computing tasks to nearby …
[HTML][HTML] A review of nature-inspired algorithms on single-objective optimization problems from 2019 to 2023
The field of nature inspired algorithm (NIA) is a vital area of research that consistently aids in
solving optimization problems. One of the metaheuristic algorithm classifications that has …
solving optimization problems. One of the metaheuristic algorithm classifications that has …
[HTML][HTML] Communication and computational resource optimization for Industry 5.0 smart devices empowered by MEC
Abstract Smart devices in Industry 5.0, such as sensors and robots, are often limited by low
battery life and finite computational resources, hindering their ability to perform complex …
battery life and finite computational resources, hindering their ability to perform complex …
[PDF][PDF] Multi-objective liver cancer algorithm: A novel algorithm for solving engineering design problems
This research introduces the Multi-Objective Liver Cancer Algorithm (MOLCA), a novel
approach inspired by the growth and proliferation patterns of liver tumors. MOLCA emulates …
approach inspired by the growth and proliferation patterns of liver tumors. MOLCA emulates …
[HTML][HTML] Enhanced whale optimization algorithm for dependent tasks offloading problem in multi-edge cloud computing
In this paper, we introduce the Enhanced Whale Optimization Algorithm (EWA) to optimize
dependent task offloading in a multi-edge cloud computing environment. Our proposed …
dependent task offloading in a multi-edge cloud computing environment. Our proposed …
Task offloading with enhanced Deep Q-Networks for efficient industrial intelligent video analysis in edge–cloud collaboration
X Ji, F Gong, N Wang, C Du, X Yuan - Advanced Engineering Informatics, 2024 - Elsevier
With the rapid development of 5G and IoT technologies, industrial video surveillance
systems face increasingly significant challenges in processing large-scale data. Traditional …
systems face increasingly significant challenges in processing large-scale data. Traditional …
[HTML][HTML] Dynamic offloading strategy for computational energy efficiency of wireless power transfer based MEC networks in industry 5.0
Wireless power transfer (WPT) has emerged as a promising solution for delivering services
to low-power Internet of Things (IoT) devices in a demand-driven manner. In this work, we …
to low-power Internet of Things (IoT) devices in a demand-driven manner. In this work, we …