An efficient self-attention-based conditional variational auto-encoder generative adversarial networks based multipath cross-layer design routing paradigm for MANET-Reference-Cited by-同舟云学术

An efficient self-attention-based conditional variational auto-encoder generative adversarial networks based multipath cross-layer design routing paradigm for MANET

Published:2024-03 Issue: Volume:238 Page:122097
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Shanmugham Kalaimani^ORCID,Rangan Rajesh,Dhatchnamurthy Saravanan,Pundir Sumit

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference22 articles.

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2. Cross layer packet drop attack detection in MANET using swarm intelligence;Bhande;International Journal of Information Technology,2021

3. Self-Attention-Based conditional variational auto-encoder generative adversarial networks for hyperspectral classification;Chen;Remote Sensing,2021

4. Gayatri, V., & Kumaran, M. S. (2022).An Improved Whale optimization Algorithm for Cross layer Neural Connection Network of MANET.Journal of Communications,17(10).

5. Gomathi, N., & Uvaneshwari, M. (2012). An Integrated Cross Layer Design to Enhance the Quality of Service of Video Streaming in Mobile Adhoc Networks.

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1. Hybrid Clustering Approach (SG-MFOA) using Multipath Cross-Layer Design in MANET Network;IETE Journal of Research;2024-06-09

2. Spacecraft Orbit Prediction Method Based on SSA-AM-LSTM;2024 9th International Conference on Computer and Communication Systems (ICCCS);2024-04-19

3. Optimizing Cross-Layer Design for Multi-Hop Wireless Networks;2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC);2024-01-29

4. A Review: An Efficient and Reliable Secure Routing Mechanism with the Prevention of Attacks in Mobile Ad-Hoc Network (MANET);Wireless Personal Communications;2023-12