Missing values are highly undesirable in real-world datasets. The missing values should be
estimated and treated during the preprocessing stage. With the expansion of nature-inspired …

Evolutionary algorithms (EAs) have become competitive solvers of a wide variety of water-
resources optimization problems. Genetic programming (GP) has become a leading EA …

Missing rainfall data has been a prevalent issue and primarily interested in hydrology and
meteorology. This research aimed to examine the capability of machine learning (ML) and …

Smart systems can be appropriately coordinated in industries to monitor and control the
performance of wastewater treatment plants to regulate their pollutant discharge levels …

In the present work, two new generalized weighted methods of imputation of missing data
are developed and tested using a daily rainfall series. The proposed methodology allows to …

Abstract Study region The Msimbazi River catchment traversing Dar es Salaam city in east-
central Tanzania. Study focus The lack of high-resolution rainfall data in cities in developing …

The prediction of granular mixtures compactness is a recurring question common to many
technical and scientific domains. Knowing the theoretical difficulties to predict the ideal …

High-resolution modelling is needed to improve the understanding and management of
storm water in cities. It requires data, which is not always available; hence the growing …

This study, through extensive experiments and mathematical modeling, reveals that other
than retention time and wastewater temperature (T w), atmospheric parameters also play …

Despite the extensive use of constructed wetland (CW) as an effective method for domestic
wastewater treatment, there is lack of clarity in arriving at well-defined design guidelines …