2 citations · 6 across the 4 of their papers we have counts for
4 papers
Imbalanced Classification In Faulty Turbine Data: New Proximal Policy Optimization
Mohammad Hossein Modirrousta, Mahdi Aliyari Shoorehdeli, Mostafa Yari +1
There is growing importance to detecting faults and implementing the best methods in industrial and real-world systems. We are searching for the most trustworthy and practical data…
Analysis of Anomalous Behavior in Network Systems Using Deep Reinforcement Learning with CNN Architecture
Mohammad Hossein Modirrousta, Parisa Forghani Arani, Mahdi Aliyari Shoorehdeli
In order to gain access to networks, different types of intrusion attacks have been designed, and the attackers are working on improving them. Computer networks have become increas…
DQLAP: Deep Q-Learning Recommender Algorithm with Update Policy for a Real Steam Turbine System
M. H. Modirrousta, M. Aliyari Shoorehdeli, M. Yari +1
In modern industrial systems, diagnosing faults in time and using the best methods becomes more and more crucial. It is possible to fail a system or to waste resources if faults ar…
Network Intrusion Detection with Limited Labeled Data Using Self-supervision
S. Lotfi, M. Modirrousta, S. Shashaani +1
With the increasing dependency of daily life over computer networks, the importance of these networks security becomes prominent. Different intrusion attacks to networks have been…