Citing Articles For: Defending Smart Electrical Power Grids against Cyberattacks with Deep -Learning

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Keying Li, Ming Gu, Bo Wang, Tingting Pan, Jiahang Tang, and Junjiang He

Detecting Attacks and Estimating States of Power Grids from Partial Observations with Machine Learning

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Stock market trading via actor-critic reinforcement learning and adaptable data structure

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Repetitive Backdoor Attacks and Countermeasures for Smart Grid Reinforcement Incremental Learning

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Evaluating Electricity Demand Elasticity From a Social Perspective: Implications for Sustainable Development and Urban Resilience

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Stochastic Economic–Resilience Management of Combined Cooling, Heat, and Power-Based Microgrids in a Multi-Objective Approach

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The deep learning applications in IoT-based bio- and medical informatics: a systematic literature review

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Advancing Active Suspension Control With TD3-PSC: Integrating Physical Safety Constraints Into Deep Reinforcement Learning

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Multi-Agent Transformer Networks With Graph Attention

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Comprehensive Overview of Reward Engineering and Shaping in Advancing Reinforcement Learning Applications

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Scheduled Curiosity-Deep Dyna-Q: Efficient Exploration for Dialog Policy Learning

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Machine Learning-Based Japanese Spot Market Price Forecasting Considering the Solar Contribution

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Leveraging Deep Reinforcement Learning Technique for Intrusion Detection in SCADA Infrastructure

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Physics-informed line graph neural network for power flow calculation

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Adaptive network approach to exploration–exploitation trade-off in reinforcement learning

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Heterogeneous reinforcement learning for defending power grids against attacks

Mohammadamin Moradi, Shirin Panahi, Zheng-Meng Zhai, Yang Weng, John Dirkman, and Ying-Cheng Lai

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Preferential Cyber Defense for Power Grids

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Electromyography Based Gesture Decoding Employing Few-Shot Learning, Transfer Learning, and Training From Scratch

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Enhanced Experience Prioritization: A Novel Upper Confidence Bound Approach

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Non-Intrusive Load Identification Method Based on Self-Supervised Regularization

Ruifeng Zhao, Jiangang Lu, Bo Liu, Zhiwen Yu, Yanru Ren, and Wenjie Zheng

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Network-Wide Traffic Signal Control Based on MARL With Hierarchical Nash-Stackelberg Game Model

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IEEE Access 11 145085 (2023)

Countering Evasion Attacks for Smart Grid Reinforcement Learning-Based Detectors

Ahmed T. El-Toukhy, Mohamed M. E. A. Mahmoud, Atef H. Bondok, Mostafa M. Fouda, and Maazen Alsabaan

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Medical image analysis using deep learning algorithms

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Front. Neurosci. 17 1256351 (2023)

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Articles Citing

Defending Smart Electrical Power Grids against Cyberattacks with Deep $Q$ -Learning

No title available

Detecting Attacks and Estimating States of Power Grids from Partial Observations with Machine Learning

Stock market trading via actor-critic reinforcement learning and adaptable data structure

Repetitive Backdoor Attacks and Countermeasures for Smart Grid Reinforcement Incremental Learning

Evaluating Electricity Demand Elasticity From a Social Perspective: Implications for Sustainable Development and Urban Resilience

Stochastic Economic–Resilience Management of Combined Cooling, Heat, and Power-Based Microgrids in a Multi-Objective Approach

The deep learning applications in IoT-based bio- and medical informatics: a systematic literature review

Advancing Active Suspension Control With TD3-PSC: Integrating Physical Safety Constraints Into Deep Reinforcement Learning

Multi-Agent Transformer Networks With Graph Attention

Comprehensive Overview of Reward Engineering and Shaping in Advancing Reinforcement Learning Applications

Enhanced Bitcoin Price Direction Forecasting With DQN

Scheduled Curiosity-Deep Dyna-Q: Efficient Exploration for Dialog Policy Learning

Machine Learning-Based Japanese Spot Market Price Forecasting Considering the Solar Contribution

Leveraging Deep Reinforcement Learning Technique for Intrusion Detection in SCADA Infrastructure

Physics-informed line graph neural network for power flow calculation

Adaptive network approach to exploration–exploitation trade-off in reinforcement learning

Heterogeneous reinforcement learning for defending power grids against attacks

Preferential Cyber Defense for Power Grids

Electromyography Based Gesture Decoding Employing Few-Shot Learning, Transfer Learning, and Training From Scratch

Enhanced Experience Prioritization: A Novel Upper Confidence Bound Approach

Non-Intrusive Load Identification Method Based on Self-Supervised Regularization

Network-Wide Traffic Signal Control Based on MARL With Hierarchical Nash-Stackelberg Game Model

Countering Evasion Attacks for Smart Grid Reinforcement Learning-Based Detectors

Medical image analysis using deep learning algorithms

Trends in using deep learning algorithms in biomedical prediction systems

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