Load Probability Density Forecasting Under FDI Attacks Based on Double-Layer LSTM Quantile Regression

Accurate load prediction is critical for boosting high-quality electricity use, as well as safety in energy and power systems. However, the power system is fraught with uncertainty, and cyber-attacks on electrical loads result in inaccurate estimates. In this study, a probability density prediction...

Täydet tiedot

Bibliografiset tiedot

Päätekijät:	Pei Zhao, Jie Zhang, Guang Ling
Aineistotyyppi:	Artigo
Kieli:	Inglês
Julkaistu:	MDPI AG 2024-12-01
Sarja:	Energies
Aiheet:	FDI attack double-layer LSTM quantile regression load probability density forecasting kernel density estimation
Linkit:	https://www.mdpi.com/1996-1073/17/24/6211
Tagit:	Lisää tagi Ei tageja, Lisää ensimmäinen tagi!