Tag: machine learning

WALKER PRESENTS AT UF 2021 UNDERGRADUATE RESEARCH SYMPOSIUM!

Congratulations to our labmate, Sarah Walker! Sarah presented her work, titled “Divergence Regulated Encoder Network for Joint Dimensionality Reduction and Classification” at UF’s 2021 Undergraduate Research Virtual Symposium.  The virtual symposium featured outstanding undergraduate researchers across all colleges at UF.… Read More

DIVERGENCE REGULATED ENCODER NETWORK FOR JOINT DIMENSIONALITY REDUCTION AND CLASSIFICATION

Abstract: In this paper, we investigate performing joint dimensionality reduction and classification using a novel histogram neural network. Motivated by a popular dimensionality reduction approach, t-Distributed Stochastic Neighbor Embedding (t-SNE), our proposed method incorporates a classification loss computed on samples… Read More

STATE ESTIMATOR AND MACHINE LEARNING ANALYSIS OF RESIDUAL DIFFERENCES TO DETECT AND IDENTIFY FDI AND PARAMETER ERRORS IN SMART GRIDS

Abstract: In the modern Smart Grid (SG), cyber-security is an increasingly important topic of research. An attacker can mislead the State Estimation (SE) process through a False Data Injection (FDI) on real-time measurement values or they can attack the parameters… Read More

A NETWORK PARAMETER DATABASE FDI CORRECTION PHYSICS-BASED MODEL: A MACHINE LEARNING SYNTHETIC MEASUREMENT BASED APPROACH

Abstract: Concerning power systems, real-time monitoring of cyber–physical security, false data injection attacks on wide-area measurements are of major concern. However, the database of the network parameters is just as crucial to the state estimation process. Maintaining the accuracy of… Read More