Power System Anomaly Detection and Classification Utilizing Wls-Ekf State Estimation and Machine Learning

POWER SYSTEM STATE ESTIMATION A. Power System State Estimation The conventional method for power system state estimation is the weight least squares (WLS) state estimation

This paper proposes the stochastic tabu search (STS) for improving the measurement scheme for power system state estimation. If the original measured scheme is not observable, the additional measurements with minimum number of measurements are added into the system by STS so that there is no critical measurement pair. The random bit flipping and bit exchanging perturbations are used for generat...

Power System State Estimation Using Weighted Least Squares (WLS) and Regularized Weighted Least Squares(RWLS) Method

In this paper, a new formulation for power system state estimation is proposed. The formulation is based on regularized least squares method which uses the principle of Thikonov’s regularization to overcome the limitations of conventional state estimation methods. In this approach, the mathematical unfeasibility which results from the lack of measurements in case of ill-posed problems is elimin...

Anomaly detection with Machine learning

A PAXOS based State Machine Replication System for Anomaly Detection

A number of systems in recent times suffer from attacks like DDoS and Ping of Death. Such attacks result in loss of critical system resources and CPU cycles, as these compromised systems behave in an abnormal manner. The effect of such abnormalities is worse in case of compromised systems handling financial transaction, since it leads to severe monetary losses. In this paper we propose a system...

Anomaly Detection System For Healthcare Resource Usage in Machine Learning

Data mining approaches have been widely applied in the field of healthcare. Patient Medical Records contains vast clinical informations about patient conditions along with treatment and its procedure .Systematic healthcare utilization analysis use these observational datas to guide resource planning and improve the quality of care delivery while reducing cost. Here present a framework for utili...