DQRE-SCnet: A novel hybrid approach for selecting users in Federated Learning with Deep-Q-Reinforcement Learning based on Spectral Clustering

@article{Ahmadi2021DQRESCnetAN,
  title={DQRE-SCnet: A novel hybrid approach for selecting users in Federated Learning with Deep-Q-Reinforcement Learning based on Spectral Clustering},
  author={Mohsen Ahmadi and Ali Taghavirashidizadeh and Danial Javaheri and Armin Masoumian and Saeid Jafarzadeh Ghoushchi and Yaghoub Pourasad},
  journal={J. King Saud Univ. Comput. Inf. Sci.},
  year={2021},
  volume={34},
  pages={7445-7458}
}
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26 Citations
Background Citations
4
Methods Citations
6

26 Citations

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This research proposes a parallelization-based approach to improve the performance of the Apriori algorithm in repetitive mining patterns on network topologies and concludes that this approach provides acceptable efficiency in terms of evaluation criteria such as energy consumption, network lifetime, and runtime compared to other methods.

DCNN-GCM: A Deep CNN and Granger Causality Models for Forecasting Welfare Level of Energy-Producing Countries and Evaluating the Relationship between Energy Consumption and Sustainable Economic Welfare

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A parallel hybrid Arithmetic Optimization Algorithm and Salp Swarm Algorithm for the optimal sizing and placement of DGs in the Radial Distribution Networks (RDNs) and the proposed parallel hybrid AOASSA enables the mutual benefit of both algorithms.

Extend the lifetime of wireless sensor networks by modifying cluster-based data collection

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Analysis of the attack and its solution in wireless sensor networks

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