Application of Photoelectric Conversion Technology in Photoelectric Signal Sampling System DOI
Guobin Zhao, Hui Zhao, Jian Zhang

и другие.

Archives of Computational Methods in Engineering, Год журнала: 2024, Номер unknown

Опубликована: Апрель 30, 2024

Язык: Английский

Research on Image Recognition and Classification Algorithms in Cloud Computing Environment Based on Deep Neural Networks DOI Creative Commons

Zihang Jia

IEEE Access, Год журнала: 2025, Номер 13, С. 19728 - 19754

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

1

Evolution of Swarm Intelligence: A Systematic Review of Particle Swarm and Ant Colony Optimization Approaches in Modern Research DOI
Rahul Priyadarshi, Ravi Kumar

Archives of Computational Methods in Engineering, Год журнала: 2025, Номер unknown

Опубликована: Март 18, 2025

Язык: Английский

Процитировано

0

Policy Framework for Realizing Net-Zero Emission in Smart Cities DOI

Peiying Wang,

Rahul Priyadarshi

Archives of Computational Methods in Engineering, Год журнала: 2024, Номер unknown

Опубликована: Апрель 30, 2024

Язык: Английский

Процитировано

3

Multi-Objective Optimization for Coverage and Connectivity in Wireless Sensor Networks DOI
Rahul Priyadarshi, Raj Vikram,

ZeKun Huang

и другие.

Опубликована: Июнь 26, 2024

Язык: Английский

Процитировано

3

Graph Neural Networks for Routing Optimization: Challenges and Opportunities DOI Open Access
Weiwei Jiang, Haoyu Han, Yang Zhang

и другие.

Sustainability, Год журнала: 2024, Номер 16(21), С. 9239 - 9239

Опубликована: Окт. 24, 2024

In this paper, we explore the emerging role of graph neural networks (GNNs) in optimizing routing for next-generation communication networks. Traditional protocols, such as OSPF or Dijkstra algorithm, often fall short handling complexity, scalability, and dynamic nature modern network environments, including unmanned aerial vehicle (UAV), satellite, 5G By leveraging their ability to model topologies learn from complex interdependencies between nodes links, GNNs offer a promising solution distributed scalable optimization. This paper provides comprehensive review latest research on GNN-based methods, categorizing them into supervised learning modeling, optimization, reinforcement tasks. We also present detailed analysis existing datasets, tools, benchmarking practices. Key challenges related real-world deployment, explainability, security are discussed, alongside future directions that involve federated learning, self-supervised online techniques further enhance GNN applicability. study serves first survey aiming inspire practical applications

Язык: Английский

Процитировано

3

Application of Photoelectric Conversion Technology in Photoelectric Signal Sampling System DOI
Guobin Zhao, Hui Zhao, Jian Zhang

и другие.

Archives of Computational Methods in Engineering, Год журнала: 2024, Номер unknown

Опубликована: Апрель 30, 2024

Язык: Английский

Процитировано

0