AI Medical Compendium Journal:
Environmental management

Showing 1 to 6 of 6 articles

Staying for food by urban birds: Insights from neural network analysis into adaptive strategies.

Environmental management
Previous work showed that animals have demonstrated remarkable adaptability by actively integrating into urban environments. However, there is no essential difference between urban and rural areas but food availability. The behavioral mechanisms and ...

Long-term Evaluation of Machine Learning Based Methods for Air Emission Monitoring.

Environmental management
Machine learning (ML) techniques have been researched and used in various environmental monitoring applications. Few studies have reported the long-term evaluation of such applications. Discussions regarding the risks and regulatory frameworks of ML ...

Monitoring the Spatial Distribution of Cover Crops and Tillage Practices Using Machine Learning and Environmental Drivers across Eastern South Dakota.

Environmental management
The adoption of conservation agriculture methods, such as conservation tillage and cover cropping, is a viable alternative to conventional farming practices for improving soil health and reducing soil carbon losses. Despite their significance in miti...

A Framework to Prioritize the Public Expectations from Water Treatment Plants based on Trapezoidal Type-2 Fuzzy Ahp Method.

Environmental management
Water treatment plants play a major role in the cycle of water recovery and reuse. Besides the benefits of water treatment plants, they have a great impact on the environment, social life, economy, and natural habitats. In this sense, decision-makers...

Optimal Selection of Sewage Treatment Technologies in Town Areas: A Coupled Multi-Criteria Decision-Making Model.

Environmental management
In recent years, the development of sewage treatment technologies has made many treatment options available in towns. Selecting the most appropriate alternative (MAA) can make the best use of existing resources to achieve the optimal effect, which ha...

Spatiotemporal Variation Assessment and Improved Prediction Of Cyanobacteria Blooms in Lakes Using Improved Machine Learning Model Based on Multivariate Data.

Environmental management
Cyanobacterial blooms in shallow lakes pose a significant threat to aquatic ecosystems and public health worldwide, highlighting the urgent need for advanced predictive methodologies. As impounded lakes along the Eastern Route of the South-to-North W...