The rapid increase in both the quantity and complexity of data that are being generated daily
in the field of environmental science and engineering (ESE) demands accompanied …

Machine learning (ML) is increasingly used in environmental research to process large data
sets and decipher complex relationships between system variables. However, due to the …

The complexity and dynamics of the environment make it extremely difficult to directly predict
and trace the temporal and spatial changes in pollution. In the past decade, the …

We humans are curious animals. While other animals generally live in balance with their
respective ecosystems, we almost seem to go out of our way to tip that balance in our favor …

Civil engineering is a branch of engineering that deals with the design, construction, and
maintenance of the built environment, including structures such as buildings, roads, bridges …

Recent advances in machine learning methods, along with successful applications across a
wide variety of fields such as planetary science and bioinformatics, promise powerful new …

Water resources of desired quality and quantity are the foundation for human survival and
sustainable development. To better protect the water environment and conserve water …

Abstract Machine learning (ML) applications in Earth and environmental sciences (EES)
have gained incredible momentum in recent years. However, these ML applications have …

Water is the most valuable natural resource on earth that plays a critical role in the socio-
economic development of humans worldwide. Water is used for various purposes, including …

Abstract Machine learning (ML) and deep learning (DL) possess excellent advantages in
data analysis (eg, feature extraction, clustering, classification, regression, image recognition …