[HTML][HTML] Self-organizing map algorithm for assessing spatial and temporal patterns of pollutants in environmental compartments: A review

S Licen, A Astel, S Tsakovski - Science of the Total Environment, 2023 - Elsevier
The evaluation of the spatial and temporal distribution of pollutants is a crucial issue to
assess the anthropogenic burden on the environment. Numerous chemometric approaches …

[HTML][HTML] Determining nitrate and sulfate pollution sources and transformations in a coastal aquifer impacted by seawater intrusion—a multi-isotopic approach …

JA Torres-Martínez, A Mora, J Mahlknecht… - Journal of Hazardous …, 2021 - Elsevier
Over the past few decades, the La Paz aquifer system in Baja California Sur, Mexico, has
been under severe pressure due to overexploitation for urban water supply and agriculture; …

Using a linear discriminant analysis (LDA)-based nomenclature system and self-organizing maps (SOM) for spatiotemporal assessment of groundwater quality in a …

V Amiri, K Nakagawa - Journal of Hydrology, 2021 - Elsevier
In this study, a linear discriminant analysis (LDA)-based nomenclature system have been
used for the classification of groundwater samples in a coastal aquifer. The capability of …

[HTML][HTML] Mapping homogeneous regions for flash floods using machine learning: A case study in Jiangxi province, China

R Zhang, Y Chen, X Zhang, Q Ma, L Ren - International Journal of Applied …, 2022 - Elsevier
Regionalization of flash floods aims to partition a geographical space into homogeneous
regions in which flash floods have similar generation mechanism. In this paper, we present a …

Unraveling the occurrence of contaminants of emerging concern in groundwater from urban setting: A combined multidisciplinary approach and self-organizing maps

PHP Stefano, A Roisenberg, MR Santos, MA Dias… - Chemosphere, 2022 - Elsevier
In recent decades, changes in human behavior and new technologies have introduced
thousands of new compounds into the environment called “contaminants of emerging …

Development of a sensitivity analysis framework for aquatic biogeochemical models using machine learning

H Cai, Y Shimoda, J Mao, GB Arhonditsis - Ecological Informatics, 2023 - Elsevier
Our evolving understanding of ecosystem functioning along with the advent of computational
power have paved the way for the development of complex mathematical models that …

Unravelling groundwater time series patterns: Visual analytics-aided deep learning in the Namoi region of Australia

SR Clark - Environmental Modelling & Software, 2022 - Elsevier
Understanding the sustainability of current groundwater extractions is critical in the face of
changing climate and anthropogenic conditions, but this proves challenging in areas with …

Dynamic patterns and potential drivers of river water quality in a coastal city: Insights from a machine-learning-based framework and water management

Y Huang, S Chen, X Tang, C Sun, Z Zhang… - Journal of Environmental …, 2024 - Elsevier
River water quality continues to deteriorate under the coupled effects of climate change and
human activities. Machine learning (ML) is a promising approach for analyzing water quality …

[HTML][HTML] The whole is greater than the sum of its parts: Using cognitive profiles to predict academic achievement

JW Younger, S Schaerlaeken, JA Anguera… - Trends in Neuroscience …, 2024 - Elsevier
Abstract Background Executive functions (EFs) are thought to work in concert to support
academic skill. However, EFs are often examined independently, obscuring their symbiotic …

Mapping of user-perceived landscape types and spatial distribution using crowdsourced photo data and machine learning: Focusing on Taeanhaean National Park

S Lee, Y Son - Journal of Outdoor Recreation and Tourism, 2023 - Elsevier
User perception of protected areas is a valuable set of information for monitoring and
managing those areas. To refer to the management direction of protected areas, various …