Actor‐critic (AC) methods have emerged as an important class of reinforcement learning
(RL) paradigm that enables model‐free control by acting on a process and learning from the …

Cyber attacks have evolved, making predicting and preventing their occurrence difficult. The
complexity of cyber threats has contributed to the development of technology-intensive …

The paper analyses a control scheme aided by LSTM networks for the delayed bilateral
teleoperation system of a skid-steering wheeled mobile robot. The strategy implemented at …

This study investigates using deep reinforcement learning (DRL) with proportional-integral-
derivative (PID) control for temperature cascade control in a fluidized bed reactor within a …

Cold rolling is an important part of the iron and steel industry, and the unsteady rolling
process of cold rolling usually brings significant influences on the stability of product quality …

Steam injection is a popular technique to enhance oil recovery in mature oil fields. However,
the conventional approach of using a constant steam rate over an extended period can lead …

This paper presents a learning-based control strategy for non-linear throttle valves with an
asymmetric hysteresis leading to a near-optimal controller. We start with a carefully tuned …

Current approaches for monitoring machine health (SOH) and effective prognostics depend
on the extensive use of complete degradation data trajectories, implying the reliance on data …

In today's era, individuals can speak and communicate online anytime and anywhere. The
Online Group Opinion (OGO), formed by the online statements of netizens, is regarded as a …

So here we are going to study about the machine learning and automatic assistance system
in machine leering which help in the effective crowd management Machine learning (ML) is …