1 citations · 1 across the 6 of their papers we have counts for
6 papers
Dynamic Load Balancing for EV Charging Stations Using Reinforcement Learning and Demand Prediction
Hesam Mosalli, Saba Sanami, Yu Yang +2
This paper presents a method for load balancing and dynamic pricing in electric vehicle (EV) charging networks, utilizing reinforcement learning (RL) to enhance network performance…
Demand Forecasting for Electric Vehicle Charging Stations using Multivariate Time-Series Analysis
Saba Sanami, Hesam Mosalli, Yu Yang +2
As the number of electric vehicles (EVs) continues to grow, the demand for charging stations is also increasing, leading to challenges such as long wait times and insufficient infr…
Calibrated Unsupervised Anomaly Detection in Multivariate Time-series using Reinforcement Learning
Saba Sanami, Amir G. Aghdam
This paper investigates unsupervised anomaly detection in multivariate time-series data using reinforcement learning (RL) in the latent space of an autoencoder. A significant chall…
Aero-engines Anomaly Detection using an Unsupervised Fisher Autoencoder
Saba Sanami, Amir G. Aghdam
Reliable aero-engine anomaly detection is crucial for ensuring aircraft safety and operational efficiency. This research explores the application of the Fisher autoencoder as an un…
Low-Frequency Load Identification using CNN-BiLSTM Attention Mechanism
Amanie Azzam, Saba Sanami, Amir G. Aghdam
Non-intrusive Load Monitoring (NILM) is an established technique for effective and cost-efficient electricity consumption management. The method is used to estimate appliance-level…
Risk-Constrained Control of Mean-Field Linear Quadratic Systems
Masoud Roudneshin, Saba Sanami, Amir G. Aghdam
The risk-neutral LQR controller is optimal for stochastic linear dynamical systems. However, the classical optimal controller performs inefficiently in the presence of low-probabil…