[HTML][HTML] Spatial Models of Solar and Terrestrial Radiation Budgets and Machine Learning: A Review
JG García Pedreros, S Lagüela López… - Remote Sensing, 2024 - mdpi.com
Currently, spatial modeling is of particular relevance as it enables the understanding of the
patterns and spatial variability of an event, the monitoring and prediction of the spatial …
patterns and spatial variability of an event, the monitoring and prediction of the spatial …
Characteristics of Soil Heavy Metal Pollution and Health Risks in Chenzhou City
Y Kuang, X Chen, C Zhu - Processes, 2024 - mdpi.com
The objective of this inquiry is to illuminate the attributes of heavy metal contamination and
evaluate the potential ecological hazards inherent in the surface soil of Chenzhou City. A …
evaluate the potential ecological hazards inherent in the surface soil of Chenzhou City. A …
ChatGPT and the future of impact assessment
Like all other fields, Artificial Intelligence (AI) is expected to affect the Impact Assessment (IA)
systems worldwide. This study explores the opinions and concerns of international IA …
systems worldwide. This study explores the opinions and concerns of international IA …
Prediction of cadmium content using machine learning methods
Heavy metals are the most environmentally hazardous pollutions in agricultural soils,
threatening humans and several ecosystem services. Cadmium (Cd) is a highly toxic …
threatening humans and several ecosystem services. Cadmium (Cd) is a highly toxic …
ĐÁNH GIÁ MỨC TỰ TƯƠNG QUAN TRONG SỐ LIỆU KHÍ HẬU TẠI HAI TRẠM KHÍ TƯỢNG Ở ĐỒNG BẰNG NAM BỘ SỬ DỤNG HÀM TỰ TƯƠNG QUAN RIÊNG …
TTRÍ DŨNG - Journal of Science and Technology-IUH, 2024 - jst.iuh.edu.vn
Abstract This study used Artificial Neural Networks (ANN) and Partial autocorrelation
function (PACF) graphs to evaluate auto-correlation level in time series of climate factors …
function (PACF) graphs to evaluate auto-correlation level in time series of climate factors …