63 citations · 110 across the 10 of their papers we have counts for
10 papers
Dimensionality Increment of PMU Data for Anomaly Detection in Low Observability Power Systems
Xin Shi, Robert Qiu
Anomaly detection is an important task in power systems. To make better use of the phasor measurement unit (PMU) data collected from a low observability power system for anomaly de…
Early Anomaly Detection in Power Systems Based on Random Matrix Theory
Xin Shi, Robert Qiu
It is important for detecting the anomaly in power systems before it expands and causes serious faults such as power failures or system blackout. With the deployments of phasor mea…
Short-term Electric Load Forecasting Using TensorFlow and Deep Auto-Encoders
Xin Shi
This paper conducts research on the short-term electric load forecast method under the background of big data. It builds a new electric load forecast model based on Deep Auto-Encod…
Estimation of high-dimensional factor models and its application in power data analysis
Xin Shi, Robert Qiu
In dealing with high-dimensional data, factor models are often used for reducing dimensions and extracting relevant information. The spectrum of covariance matrices from power data…
Improving Power System State Estimation Based on Matrix-Level Cleaning
Haosen Yang, Robert C. Qiu, Lei Chu +3
Power system state estimation is heavily subjected to measurement error, which comes from the noise of measuring instruments, communication noise, and some unclear randomness. Trad…
Spatio-Temporal Correlation Analysis of Online Monitoring Data for Anomaly Detection and Location in Distribution Networks
Xin Shi, Robert Qiu, Zenan Ling +3
The online monitoring data in distribution networks contain rich information on the running states of the networks. By leveraging the data, this paper proposes a spatio-temporal co…
Adversarial Feature Learning of Online Monitoring Data for Operational Risk Assessment in Distribution Networks
Xin Shi, Robert Qiu, Tiebin Mi +2
With the deployment of online monitoring systems in distribution networks, massive amounts of data collected through them contains rich information on the operating states of the n…
Unsupervised Feature Learning for Online Voltage Stability Evaluation and Monitoring Based on Variational Autoencoder
Haosen Yang, Robert C. Qiu, Xin Shi +1
With the increase of uncertain elements in power systems and extensive deployment of online monitoring devices, it is necessary to search a more real-time and robust voltage stabil…
Early Anomaly Detection and Location in Distribution Network: A Data-Driven Approach
Xin Shi, Robert Qiu, Xing He +3
The measurement data collected from the supervisory control and data acquisition (SCADA) system installed in distribution network can reflect the operational state of the network e…
Individual Recognition in Schizophrenia using Deep Learning Methods with Random Forest and Voting Classifiers: Insights from Resting State EEG Streams
Lei Chu, Robert Qiu, Haichun Liu +3
Recently, there has been a growing interest in monitoring brain activity for individual recognition system. So far these works are mainly focussing on single channel data or fragme…