A survey on safeguarding critical infrastructures: Attacks, AI security, and future directions

KJ Raval, NK Jadav, T Rathod, S Tanwar… - International journal of …, 2024‏ - Elsevier
Technologies such as artificial intelligence (AI), blockchain, and the Internet of Things (IoT)
have converged in driving the next wave of digital revolution. Amalgamating the …

Review on the recent progress in nuclear plant dynamical modeling and control

Z Dong, Z Cheng, Y Zhu, X Huang, Y Dong, Z Zhang - Energies, 2023‏ - mdpi.com
Nuclear plant modeling and control is an important subject in nuclear power engineering,
giving the dynamic model from process mechanics and/or operational data as well as …

Implementation of deep learning methods in prediction of adsorption processes

D Skrobek, J Krzywanski, M Sosnowski… - … in Engineering Software, 2022‏ - Elsevier
The article presents deep learning methods applied to predict the mass of an adsorption bed
in the fixed and fluidized bed. The purpose of the application of this kind of bed is to improve …

Probabilistic machine-learning methods for performance prediction of structure and infrastructures through natural gradient boosting

SZ Chen, DC Feng, WJ Wang… - Journal of Structural …, 2022‏ - ascelibrary.org
The capabilities of data-driven models based on machine learning (ML) algorithms in
offering accurate predictions of structural responses efficiently have been demonstrated in …

Development and research of triangle-filter convolution neural network for fuel reloading optimization of block-type HTGRs

Z Li, J Wang, J Huang, M Ding - Applied Soft Computing, 2023‏ - Elsevier
The problem of fuel reloading optimization is very demanding, which requires to search for
the optimal suitable core configuration within a very huge solution space. To solve this …

Artificial intelligence based active and reactive power control method for single-phase grid connected hydrogen fuel cell systems

U Yilmaz, O Turksoy - International Journal of Hydrogen Energy, 2023‏ - Elsevier
In grid-connected power generation systems, power factor fluctuations caused by non-linear
power circuits used between the grid and source should be controlled with the help of …

Neural network extended state-observer for energy system monitoring

Y Zhu, Z Dong, Z Cheng, X Huang, Y Dong, Z Zhang - Energy, 2023‏ - Elsevier
Due to the complexity of industrial energy systems such as the thermal power plants,
renewable plants and batteries, energy system monitoring is gaining more and more …

Elevating hourly PM2. 5 forecasting in Istanbul, Türkiye: Leveraging ERA5 reanalysis and genetic algorithms in a comparative machine learning model analysis

S Gündoğdu, T Elbir - Chemosphere, 2024‏ - Elsevier
Rapid urbanization and industrialization have intensified air pollution, posing severe health
risks and necessitating accurate PM 2.5 predictions for effective urban air quality …

Utilization of random forest classifier and artificial neural network for predicting the acceptance of reopening decommissioned nuclear power plant

AKS Ong, YT Prasetyo, KEC Velasco, EDR Abad… - Annals of Nuclear …, 2022‏ - Elsevier
Abstract The Bataan Nuclear Power Plant (BNPP) is one of the many decommissioned
Nuclear Power Plant (NPP) globally and its reopening has led to different perceptions …

[HTML][HTML] Why are street foods consumed? A machine learning ensemble approach to assess consumption intention of street foods

ER Tacardon, AKS Ong, MJJ Gumasing - Future Foods, 2023‏ - Elsevier
Street food promotes a country's society, culture, and economy. Most studies on street food
have focused on food quality, eating habits, and eating motivation. However, despite the …