AI Medical Compendium Journal:
Environmental research

Showing 61 to 70 of 109 articles

Artificial intelligence-based forecasting model for incinerator in sulfur recovery units to predict SO emissions.

Environmental research
Pollutant emissions from chemical plants are a major concern in the context of environmental safety. A reliable emission forecasting model can provide important information for optimizing the process and improving the environmental performance. In th...

Artificial intelligence-based prediction model for the elemental occurrence form of tailings and mine wastes.

Environmental research
With the advent of the second industrial revolution, mining and metallurgical processes generate large volumes of tailings and mine wastes (TMW), which worsens global environmental pollution. Studying the occurrence of metal and metalloid elements in...

An enhanced drought forecasting in coastal arid regions using deep learning approach with evaporation index.

Environmental research
Coastal arid regions are similar to deserts, where it receives significantly less rainfall, less than 10 cm. Perhaps the world's worst natural disaster, coastal area droughts, can only be detected using reliable monitoring systems. Creating a reliabl...

Coastal Flood risk assessment using ensemble multi-criteria decision-making with machine learning approaches.

Environmental research
Coastal areas are at a higher risk of flooding, and novel changes in the climate are induced to raise the sea level. Flood acceleration and frequency have increased recently because of unplanned infrastructural conveniences and anthropogenic activiti...

Different policies constrained agricultural non-point pollutants emission trading management for water system under interval, fuzzy, and stochastic information.

Environmental research
Formulating suitable policies is essential for resources and environmental management. In this study, an agricultural pollutants emission trading management model driven by water resources and pollutants control is developed to search reasonable poli...

Data-driven modelling for assessing trophic status in marine ecosystems using machine learning approaches.

Environmental research
Assessing eutrophication in coastal and transitional waters is of utmost importance, yet existing Trophic Status Index (TSI) models face challenges like multicollinearity, data redundancy, inappropriate aggregation methods, and complex classification...

Multi-task machine learning models for simultaneous prediction of tissue-to-blood partition coefficients of chemicals in mammals.

Environmental research
Tissue-to-blood partition coefficients (P) are crucial for assessing the distribution of chemicals in organisms. Given the lack of experimental data and laborious nature of experimental methods, there is an urgent need to develop efficient predictive...

Enhancement of methane production by electrohydrolysis pretreatment for anaerobic digestion of OFMSW.

Environmental research
Hydrolysis is the most critical rate-limiting step in the anaerobic digestion (AD) process for most types of substrates. The organic fraction of municipal solid waste (OFMSW) is a rich source for the AD process because of its high degradability. In t...

Spatio-temporal fusion of meteorological factors for multi-site PM2.5 prediction: A deep learning and time-variant graph approach.

Environmental research
In the field of environmental science, traditional methods for predicting PM2.5 concentrations primarily focus on singular temporal or spatial dimensions. This approach presents certain limitations when it comes to deeply mining the joint influence o...

An interval water demand prediction method to reduce uncertainty: A case study of Sichuan Province, China.

Environmental research
Effective prediction of water demand is a prerequisite for decision makers to achieve reliable management of water supply. Currently, the research on water demand prediction focuses on point prediction method. In this study, we constructed a GA-BP-KD...