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Found 9 papers, 1 papers with code
Survey on Large Language Model-Enhanced Reinforcement Learning: Concept, Taxonomy, and Methods
With extensive pre-trained knowledge and high-level general capabilities, large language models (LLMs) emerge as a promising avenue to augment reinforcement learning (RL) in aspects such as multi-task learning, sample efficiency, and task planning.
Framework of Resilient Transmission Network Reconfiguration Considering Cyber-Attacks
Fast and reliable transmission network reconfiguration is critical in improving power grid resilience to cyber-attacks.
Power System Fault Diagnosis with Quantum Computing and Efficient Gate Decomposition
Power system fault diagnosis is crucial for identifying the location and causes of faults and providing decision-making support for power dispatchers.
Exploring Large Language Model based Intelligent Agents: Definitions, Methods, and Prospects
Intelligent agents stand out as a potential path toward artificial general intelligence (AGI).
Adapting to climate change: Long-term impact of wind resource changes on China's power system resilience
Modern society's reliance on power systems is at risk from the escalating effects of wind-related climate change.
Near Real-time CO$_2$ Emissions Based on Carbon Satellite and Artificial Intelligence
Here we provide the first method that combines the advanced artificial intelligence (AI) techniques and the carbon satellite monitor to quantify anthropogenic CO$_2$ emissions.
Fed-NILM: A Federated Learning-based Non-Intrusive Load Monitoring Method for Privacy-Protection
However, inadequate load data and the risk of power consumer privacy breaches may be encountered by local data owners during the NILM model training.
A Federated Learning Framework for Non-Intrusive Load Monitoring
The global model is generated by weighted averaging the locally-trained model weights to gather the locally-trained model information.
Super-Resolution Perception for Industrial Sensor Data
In this paper, we present the problem formulation and methodology framework of Super-Resolution Perception (SRP) on industrial sensor data.
