Given the great advancements in soft computing and data science, artificial neural network
(ANN) has been explored and applied to handle complicated problems in the field of …

Soft computing (SC), due to its high abilities to solve the complex problems with uncertainty
and multiple parameters, has been widely investigated and used, especially in structural …

The objective of this study is to develop a broadly applicable, high-precision, and robust
prediction model for the drying shrinkage of recycled aggregate concrete, a material that …

The prediction of concrete compressive strength based on mixing proportions using
statistical and machine learning techniques has gained significant attention due to its …

The challenge in harvesting Salinity Gradient Power (SGP) through pressure retarded
osmosis (PRO) requires design of high power density (PD) membranes and optimized …

The quest for energy and environmental sustainability necessitates an increasing interest in
the photocatalytic conversion of wastewater to biohydrogen. However, the complexity of the …

This study aims to reveal the potential of Light-transmitting concrete (LTC) in transmitting
natural light or sunlight, and to investigate the relationship between fibre diameter, fibre …

This research project aims to investigate the efficacy of artificial neural networks (ANN) in
mapping dry flue gas desulphurization (DFGD). Bayesian regularization (BR) and …

Modelling, predicting, and forecasting hydrological phenomena like groundwater have been
one of the prominent applications of artificial intelligence techniques. Using Multi-Layer …

This study proposes a long-term strain prediction model for concrete structures using
weather data. In the proposed model, the relationship between weather and the strain data …