Machine learning: new ideas and tools in environmental science and engineering
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 …
in the field of environmental science and engineering (ESE) demands accompanied …
Microplastic abundance, characteristics, and removal in wastewater treatment plants in a coastal city of China
Studying the abundance, characteristics, and removal of microplastics (MPs) in wastewater
treatment plants (WWTPs) in coastal cities is of great significance for understanding the …
treatment plants (WWTPs) in coastal cities is of great significance for understanding the …
Evapotranspiration evaluation models based on machine learning algorithms—A comparative study
F Granata - Agricultural Water Management, 2019 - Elsevier
The constant need to increase agricultural production, together with the more and more
frequent drought events in many areas of the world, requires a more careful assessment of …
frequent drought events in many areas of the world, requires a more careful assessment of …
Simulation and forecasting of streamflows using machine learning models coupled with base flow separation
Efficient simulation of rainfall-runoff relationships is one of the most complex problems owing
to the high number of interrelated hydrological processes. It is well-known that machine …
to the high number of interrelated hydrological processes. It is well-known that machine …
Reliability evaluation of groundwater quality index using data-driven models
A trustworthy evaluation of the groundwater quality situations for different usages (ie,
drinking, industry, and agriculture) can definitely improve the management of groundwater …
drinking, industry, and agriculture) can definitely improve the management of groundwater …
Artificial Intelligence models for prediction of the tide level in Venice
The city of Venice is an extraordinary architectural, artistic and cultural heritage.
Unfortunately, its conservation is increasingly threatened by particularly significant high …
Unfortunately, its conservation is increasingly threatened by particularly significant high …
A graphically based machine learning approach to predict secondary schools performance in Tunisia
S Rebai, FB Yahia, H Essid - Socio-Economic Planning Sciences, 2020 - Elsevier
The main purpose of this paper is to identify the key factors that impact schools' academic
performance and to explore their relationships through a two-stage analysis based on a …
performance and to explore their relationships through a two-stage analysis based on a …
Artificial intelligence based approaches to evaluate actual evapotranspiration in wetlands
Wetlands are extraordinary ecosystems and important climate regulators that also contribute
to reduce natural disaster risk. Unfortunately, wetlands are declining much faster than …
to reduce natural disaster risk. Unfortunately, wetlands are declining much faster than …
Combined advanced oxidation dye-wastewater treatment plant: design and development with data-driven predictive performance modeling
The recalcitrant nature of the industrial dyes poses a significant challenge to existing
treatment technologies due to the stringent environmental regulations. This combined with …
treatment technologies due to the stringent environmental regulations. This combined with …
The integration of nature-inspired algorithms with least square support vector regression models: application to modeling river dissolved oxygen concentration
The current study investigates an improved version of Least Square Support Vector
Machines integrated with a Bat Algorithm (LSSVM-BA) for modeling the dissolved oxygen …
Machines integrated with a Bat Algorithm (LSSVM-BA) for modeling the dissolved oxygen …