Deep learning-based electricity theft prediction in non-smart grid environments. [PDF]
Saqib SM +6 more
europepmc +1 more source
This paper presents an integrated AI‐driven cardiovascular platform unifying multimodal data, predictive analytics, and real‐time monitoring. It demonstrates how artificial intelligence—from deep learning to federated learning—enables early diagnosis, precision treatment, and personalized rehabilitation across the full disease lifecycle, promoting a ...
Mowei Kong +4 more
wiley +1 more source
Stealthy data integrity attack identification in smart grid networks utilizing deep denoising autoencoder. [PDF]
Kousar A +4 more
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Optimal adaptive heuristic algorithm based energy optimization with flexible loads using demand response in smart grid. [PDF]
Alghamdi H +5 more
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Enhancing Power Quality in Solar-Integrated Smart Grids for EV Systems through Smart Controller
V Raveendra Reddy +5 more
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Security risk models against attacks in smart grid using big data and artificial intelligence. [PDF]
Yasin Ghadi Y +6 more
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Deep learning-driven hybrid model for short-term load forecasting and smart grid information management. [PDF]
Wen X, Liao J, Niu Q, Shen N, Bao Y.
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Attention Based Energy Demand Forecasting in Smart Grid Environments
Yunus Emre Işıkdemir, Fuat Akal
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A comprehensive review of recent developments in smart grid through renewable energy resources integration. [PDF]
Ohanu CP, Rufai SA, Oluchi UC.
europepmc +1 more source
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IEEE Transactions on Smart Grid, 2023The rapid development of information and communications technology has enabled the use of digital-controlled and software-driven distributed energy resources (DERs) to improve the flexibility and efficiency of power supply, and support grid operations ...
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