The current research was an effort to critically review all approaches used for membrane
fouling control in the membrane bioreactors treating water and wastewater. The first …

This paper critically reviews all artificial intelligence (AI) and machine learning (ML)
techniques for the better control of membrane fouling in filtration processes, with the focus …

Accurate simulation of wastewater effluent parameters is a vital concern to reduce the
operational costs of a wastewater treatment plant. In this way, a reliable predictive model is a …

Research and development activities on standalone systems of membrane bioreactors and
electrochemical reactors for wastewater treatment have been intensified recently. However …

Stringent regulations and deteriorating source water quality could greatly influence the water
production capacity of drinking water treatment plants (DWTPs). Using models to predict the …

The distribution and abundance of Phlebotomus papatasi, the primary vector of zoonotic
cutaneous leishmaniasis in most semi-/arid countries, is a major public health challenge …

Artificial intelligence (AI) and machine learning (ML) are novel techniques to detect hidden
patterns in environmental data. Despite their capabilities, these novel technologies have not …

Heavy metals and emerging engineered nanoparticles (ENPs) are two current
environmental concerns that have attracted considerable attention. Cerium oxide …

This study evaluates and models the impacts of employing biofilm carriers in sequencing
batch reactors (SBR). A neural network (NN) was used to predict contaminants in the effluent …

Accurate streamflow prediction is of significant importance in watershed management and
has been attracting a lot of research interest. Hybrid hydrological models that employ …