[HTML][HTML] Deep learning for intelligent demand response and smart grids: A comprehensive survey
Electricity is one of the mandatory commodities for mankind today. To address challenges
and issues in the transmission of electricity through the traditional grid, the concepts of smart …
and issues in the transmission of electricity through the traditional grid, the concepts of smart …
Edge Offloading in Smart Grid
The management of decentralized energy resources and smart grids needs novel data-
driven low-latency applications and services to improve resilience and responsiveness and …
driven low-latency applications and services to improve resilience and responsiveness and …
Decentralized federated learning based on blockchain: concepts, framework, and challenges
Decentralized federated learning integrates advanced technologies, including distributed
computing and secure encryption methodologies, to facilitate a robust and efficient …
computing and secure encryption methodologies, to facilitate a robust and efficient …
Decentralized asynchronous adaptive federated learning algorithm for securely prediction of distributed power data
Q Li, D Liu, H Cao, X Liao, X Lai, W Cui - Frontiers in Energy …, 2024 - frontiersin.org
Introduction: Improving the precision and real-time speed of electricity data prediction while
safeguarding data privacy and security holds immense significance for all power system …
safeguarding data privacy and security holds immense significance for all power system …
Unlocking a Promising Future: Integrating Blockchain Technology and FL-IoT in the Journey to 6G
The rapid advancement of technology has set higher standards for the next generation of
wireless communication networks, known as 6G. These networks go beyond the simple task …
wireless communication networks, known as 6G. These networks go beyond the simple task …
Energy Demand Forecasting for Electric Vehicles Using Blockchain-Based Federated Learning
The widespread adoption of electric cars (EVs) can be attributed to their many advantages
over conventional gas-powered automobiles. However, there may be difficulties in …
over conventional gas-powered automobiles. However, there may be difficulties in …
Towards trustworthy federated learning: a blockchain-based architecture for auditing, traceability, and verification
H Gao, X Pan, X Zhang, K Ye… - … on Computer Science …, 2023 - spiedigitallibrary.org
The 14th Five-Year Plan proposes the objective of expediting digital development and
constructing a digital China, aiming to minimize the reliance on physical travel while …
constructing a digital China, aiming to minimize the reliance on physical travel while …
A Non-centralized Federated Learning Architecture to Obtain Accurate Privacy Preserving Results
J Bobadilla, A Gutierrez, S Alonso - Proceedings of the 2024 10th …, 2024 - dl.acm.org
Federated learning was introduced in 2016 by Google researchers to train machine learning
models to preserve user privacy. Basically, applying the federated learning concept, the …
models to preserve user privacy. Basically, applying the federated learning concept, the …
Fedwoa: A Federated Learning Model with the Whale Optimization Algorithm for Renewable Energy Prediction
Privacy is important when dealing with sensitive personal information in machine learning
models, which require large data sets for training. In the energy field, access to household's …
models, which require large data sets for training. In the energy field, access to household's …