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Environmental Monitoring

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Microplastics and Trash Cleaning and Harmonization (MaTCH): Semantic Data Ingestion and Harmonization Using Artificial Intelligence.

Environmental science & technology
With the rapid expansion of microplastic research and reliance on semantic descriptors, there is an increasing need for plastic pollution data harmonization. Data standards have been developed but are seldom implemented across research sectors, geogr...

Multi-temporal image analysis of wetland dynamics using machine learning algorithms.

Journal of environmental management
Wetlands play a crucial role in enhancing groundwater quality, mitigating natural hazards, controlling erosion, and providing essential habitats for unique flora and wildlife. Despite their significance, wetlands are facing decline in various global ...

Improving the construction and prediction strategy of the Air Quality Health Index (AQHI) using machine learning: A case study in Guangzhou, China.

Ecotoxicology and environmental safety
Effectively capturing the risk of air pollution and informing residents is vital to public health. The widely used Air Quality Index (AQI) has been criticized for failing to accurately represent the non-threshold linear relationship between air pollu...

Mining soil heavy metal inversion based on Levy Flight Cauchy Gaussian perturbation sparrow search algorithm support vector regression (LSSA-SVR).

Ecotoxicology and environmental safety
Soil heavy metal pollution in mining areas poses severe challenges to the ecological environment. In recent years, machine learning has been widely used in heavy metal inversion by hyperspectral data. However, deterministic algorithms and probabilist...

Downscaling MODIS evapotranspiration into finer resolution using machine learning approach on a small scale, Ribb watershed, Ethiopia.

Environmental monitoring and assessment
By monitoring evapotranspiration (ET), the exchange of water and energy between the soil, plants, and the atmosphere can be controlled. Routine estimations of ET on a daily, monthly, and seasonal basis can give relevant information on small-scale agr...

Advanced Low-Cost Technology for Assessing Metal Accumulation in the Body of a Metropolitan Resident Based on a Neural Network Model.

Sensors (Basel, Switzerland)
This study is devoted to creating a neural network technology for assessing metal accumulation in the body of a metropolis resident with short-term and long-term intake from anthropogenic sources. Direct assessment of metal retention in the human bod...

Assessment of groundwater quality variation characteristics and influencing factors in an intensified agricultural area: An integrated hydrochemical and machine learning approach.

Journal of environmental management
The decline in groundwater quality in intensive agricultural areas in recent years, driven by environmental change and intensified human activity, poses a significant threat to agricultural production and public health, requiring attention and effect...

Development of a deep learning-based feature stream network for forecasting riverine harmful algal blooms from a network perspective.

Water research
Global increases in the occurrence of harmful algal blooms (HABs) are of major concern in water quality and resource management. A predictive model capable of quantifying the spatiotemporal associations between HABs and their influencing factors is r...

Big data from population surveys and environmental monitoring-based machine learning predictions of indoor PM in 22 cities in China.

Ecotoxicology and environmental safety
Many studies have confirmed that PM exposure can cause a variety of diseases. Because people spend most of their time indoors, exposure to PM in indoor environments is critical to population health. Large-population, long-term, continuous, and accura...

Efficient High Heating Value estimation using Latin Hypercube Sampling and Artificial Neural Network-based approach.

Environmental monitoring and assessment
To maximize energy recovery in waste-to-energy (WTE) systems, the High Heating Value (HHV) of municipal solid waste (MSW) must be accurately estimated. To forecast the HHV of MSW, this study proposes a unique method that combines an Artificial Neural...