Inorganic and organic contaminants, such as fertilisers, heavy metals, and dyes, are the
primary causes of water pollution. The field of artificial intelligence (AI) has received …

The objective of this work is to compare the efficiency of three computational intelligence
techniques: Artificial Neural Networks (ANNs), Support Vector Machines (SVMs) and …

In the present study, hybrid prediction models were used to estimate the adsorption of
ammonium from landfill leachate by using zeolite in batch and column systems. The effects …

This paper illustrates the application of artificial neural network (ANN) for prediction of
performances in competitive adsorption of phenol and resorcinol from aqueous solution by …

Artificial intelligence (AI) has emerged as a powerful tool to resolve real-world problems and
has gained tremendous attention due to its applications in various fields. In recent years, AI …

Computation methods or molecular simulations can be used to identify materials with high
adsorption capacity for wastewater treatment rapidly. They can also provide complementary …

Universal differential equations are a concept in scientific machine learning that leverages
the potential of the universal approximator theorem and the physical knowledge of a given …

Biobutanol has attracted significant interest in recent decades and is seriously considered
as a potential biofuel to partly replace gasoline. However, some production challenges must …

This paper investigates multiple methods of machine learning for an application of surrogate
modeling and optimization of an experimentally validated pressure swing adsorption model …

Predictive models are useful tools for aqueous adsorption research; existing models such as
multilinear regression (MLR), however, can only predict adsorption under specific …