Bridging data-driven and model-based approaches for process fault diagnosis and health monitoring: A review of researches and future challenges
Abstract Fault Diagnosis and Health Monitoring (FD-HM) for modern control systems have
been an active area of research over the last few years. Model-based FD-HM computational …
been an active area of research over the last few years. Model-based FD-HM computational …
AIoT for sustainable manufacturing: Overview, challenges, and opportunities
The integration of IoT and AI has gained significant attention as an emerging means to
digitize manufacturing industries and drive sustainability in the context of Industry 4.0. In …
digitize manufacturing industries and drive sustainability in the context of Industry 4.0. In …
A machine learning based approach for predicting blockchain adoption in supply Chain
The purpose of this paper is to provide a decision support system for managers to predict an
organization's probability of successful blockchain adoption using a machine learning …
organization's probability of successful blockchain adoption using a machine learning …
Evolution of safety and security risk assessment methodologies towards the use of bayesian networks in process industries
PG George, VR Renjith - Process Safety and Environmental Protection, 2021 - Elsevier
Process Industries handling, producing and storing bulk amount of hazardous materials are
a major source of concern in terms of both safety and security. Safety and security cannot be …
a major source of concern in terms of both safety and security. Safety and security cannot be …
Design of experiments and focused grid search for neural network parameter optimization
The present work offers some contributions to the area of surface roughness modeling by
Artificial Neural Networks (ANNs) in machining processes. It proposes a method for an …
Artificial Neural Networks (ANNs) in machining processes. It proposes a method for an …
RAP: An end-to-end rate-based congestion control mechanism for realtime streams in the Internet
End-to-end congestion control mechanisms have been critical to the robustness and stability
of the Internet. Most of today's Internet traffic is TCP, and we expect this to remain so in the …
of the Internet. Most of today's Internet traffic is TCP, and we expect this to remain so in the …
Short‐term traffic flow prediction with linear conditional Gaussian Bayesian network
Traffic flow prediction is an essential part of intelligent transportation systems (ITS). Most of
the previous traffic flow prediction work treated traffic flow as a time series process only …
the previous traffic flow prediction work treated traffic flow as a time series process only …
Evaluating the efficacy of SVMs, BNs, ANNs and ANFIS in wave height prediction
I Malekmohamadi, MR Bazargan-Lari, R Kerachian… - Ocean …, 2011 - Elsevier
Wave Height (WH) is one of the most important factors in design and operation of maritime
projects. Different methods such as semi-empirical, numerical and soft computing-based …
projects. Different methods such as semi-empirical, numerical and soft computing-based …
Prediction of selective laser melting part quality using hybrid Bayesian network
Additive manufacturing (AM) is gaining popularity because of its ability to manufacture
complex parts in less time. Despite recent research involving designs of experiments (DOEs) …
complex parts in less time. Despite recent research involving designs of experiments (DOEs) …
Modelling and assessing seismic resilience of critical housing infrastructure system by using dynamic Bayesian approach
Seismic resilience, the ability of urban housing infrastructure to withstand and recover from
seismic events, is of paramount importance in regions prone to earthquakes. Infrastructure …
seismic events, is of paramount importance in regions prone to earthquakes. Infrastructure …