FDI Correction Physics-Based Model accepted to Applied Sciences!

Congratulations to our labmates and collaborators: Tierui Zou, Nader Aljohani, Keerthiraj Nagaraj, Sheng Zou, Cody Ruben, Arturo Bretas, Alina Zare and Janise McNair! Their paper, “A Network Parameter Database False Data Injection Correction Physics-Based Model: A Machine Learning Synthetic Measurement-Based Approach “, was recently accepted to Applied Sciences. In the paper, the authors present an overdetermined physics-based parameter false data injection correction model.

Check out the paper and key results here!