AI Medical Compendium Journal:
Environmental science and pollution research international

Showing 1 to 10 of 423 articles

An innovative machine learning approach for slope stability prediction by combining shap interpretability and stacking ensemble learning.

Environmental science and pollution research international
Accurate slope stability prediction is crucial for mitigating slope failures, but conventional methods are challenging due to their complexity and high data requirements. To overcome these limitations, researchers have used machine learning (ML) tech...

Artificial intelligence-based modeling of biogas production in a combined microbial electrolysis cell-anaerobic digestion system using artificial neural networks and adaptive neuro-fuzzy inference system.

Environmental science and pollution research international
Accurate prediction of biogas production is essential for optimizing process performance, enhancing system stability, and enabling efficient resource management in bioenergy applications. The integrated microbial electrolysis cell and anaerobic diges...

Fine extraction of multi-crop planting area based on deep learning with Sentinel- 2 time-series data.

Environmental science and pollution research international
Accurate and timely access to the spatial distribution of crops is crucial for sustainable agricultural development and food security. However, extracting multi-crop areas based on high-resolution time-series data and deep learning still faces challe...

Optimization of CO absorption into MDEA-PZ-sulfolane hybrid solution using machine learning algorithms and RSM.

Environmental science and pollution research international
This study presents the modeling and simulation of carbon dioxide (CO₂) absorption in hybrid amine solutions using machine learning algorithms and response surface methodology (RSM). The process was governed by adjustable input parameters, including ...

Management of sustainable urban green spaces through machine learning-supported MCDM and GIS integration.

Environmental science and pollution research international
This study evaluates green space suitability in İzmir's Konak district using the analytic hierarchy process, machine learning, weighted linear combination, and the technique for order preference by similarity to ideal solution methods, integrated wit...

Predictive modeling of climate change impacts using Artificial Intelligence: a review for equitable governance and sustainable outcome.

Environmental science and pollution research international
The accelerating pace of climate change poses unprecedented challenges to global ecosystems and human societies. In response, this study reviews the power of Artificial Intelligence (AI) to develop advanced predictive models for assessing the multifa...

Statistical analysis and prediction via neural networks of water quality in the Middle Paraíba do Sul (Rio de Janeiro State, Brazil) region in the period (2012-2022).

Environmental science and pollution research international
The aim of this study is to accurately predict the water quality at these points over a decade through the combined use of statistical tools and artificial intelligence. This study brings the innovative use of neural networks implemented with the GRN...

Forecasting the concentration of the components of the particulate matter in Poland using neural networks.

Environmental science and pollution research international
Air pollution is a significant global challenge with profound impacts on human health and the environment. Elevated concentrations of various air pollutants contribute to numerous premature deaths each year. In Europe, and particularly in Poland, air...

Machine learning-based prediction of unconfined compressive strength and contaminant leachability in dredged contaminated sediments for land reclamation projects.

Environmental science and pollution research international
This research investigates the application of machine learning techniques for predicting unconfined compressive strength (UCS) and contaminant leachability in dredged contaminated sediments (DCS) with implications for land reclamation projects. Tradi...

Explainable artificial intelligence-based compressive strength optimization and Life-Cycle Assessment of eco-friendly sugarcane bagasse ash concrete.

Environmental science and pollution research international
Investigations on the potential use of sustainable sugarcane bagasse ash (SCBA) as a supplementary cementitious material (SCM) in concrete production have been carried out. The paper employs model agnostic eXplainable Artificial Intelligence (XAI) to...