AI Medical Compendium Journal:
Environmental monitoring and assessment

Showing 41 to 50 of 175 articles

Mapping of high-resolution daily particulate matter (PM) concentration at the city level through a machine learning-based downscaling approach.

Environmental monitoring and assessment
PM pollution is a major global concern, especially in Vietnam, due to its harmful effects on health and the environment. Monitoring local PM levels is crucial for assessing air quality. However, Vietnam's state-of-the-art (SOTA) dataset with a 3 km r...

Modeling and predicting caffeine contamination in surface waters using artificial intelligence and standard statistical methods.

Environmental monitoring and assessment
Caffeine, considered an emerging contaminant, serves as an indicator of anthropic influence on water resources. This research employs various modeling techniques, including Artificial Neural Networks (ANN), Random Forest (RF), and more, along with hy...

Assessment of urban flood susceptibility based on a novel integrated machine learning method.

Environmental monitoring and assessment
Flood susceptibility assessment is the premise and foundation to prevent flood disaster events effectively. To accurately assess urban flood susceptibility (UFS), this study first analyzes the advantages and disadvantages of multi-layer perceptron (M...

Integrating Sentinel-1 data and machine learning for effective paddy field monitoring in Cauvery Delta Zone, Tamil Nadu, India.

Environmental monitoring and assessment
Paddy crop mapping is essential for agricultural monitoring, ensuring food security, and enhancing resource allocation. This study observes the Cauvery Delta Zone (CDZ), recognized as the rice bowl of Tamil Nadu and a crucial area for paddy farming i...

Enhancing groundwater quality prediction through ensemble machine learning techniques.

Environmental monitoring and assessment
Groundwater quality is assessed by conducting water sampling and laboratory analysis. Field-based measurements are costly and time-consuming. This study introduces a machine learning (ML)-based framework and innovative application of stacking ensembl...

Multitemporal monitoring of forest indicator species using UAV and machine learning image recognition.

Environmental monitoring and assessment
In natural restoration, it is important to improve the efficiency of monitoring. Remote sensing using unmanned aerial vehicle (UAV) platforms plays a major role in improving monitoring efficiency. UAV platforms are particularly suited for monitoring ...

Fuzzy set-based decision support system for hydrogen sulfide removal technology selection in natural gas processing: a sustainability and efficiency perspective.

Environmental monitoring and assessment
Removing hydrogen sulfide (HS) toxic and corrosive gas from the natural gas processing and utilization industry is a challenging problem for managers of these industries. This problem involves different economic, environmental, and health issues. Var...

A hybrid deep learning model-based LSTM and modified genetic algorithm for air quality applications.

Environmental monitoring and assessment
Over time, computing power and storage resource advancements have enabled the widespread accumulation and utilization of data across various domains. In the field of air quality, analyzing data and developing air quality models have become pivotal in...

Hybrid modeling techniques for predicting chemical oxygen demand in wastewater treatment: a stacking ensemble learning approach with neural networks.

Environmental monitoring and assessment
To ensure operational efficiency, promote sustainable wastewater treatment practices, and maintain compliance with environmental regulations, it is crucial to evaluate the parameters of treated effluent in wastewater treatment plants (WWTPs). Artific...

Developing novel spectral indices for precise estimation of soil pH and organic carbon with hyperspectral data and machine learning.

Environmental monitoring and assessment
Accurate soil pH and soil organic carbon (SOC) estimations are vital for sustainable agriculture, as pH affects nutrient availability, and SOC is crucial for soil health and fertility. Hyperspectral imaging provides a faster, non-destructive, and eco...