[HTML][HTML] Recent trends in AI-based intelligent sensing
In recent years, intelligent sensing has gained significant attention because of its
autonomous decision-making ability to solve complex problems. Today, smart sensors …
autonomous decision-making ability to solve complex problems. Today, smart sensors …
Hyperspectral inversion of soil heavy metals in Three-River Source Region based on random forest model
W Zhou, H Yang, L Xie, H Li, L Huang, Y Zhao, T Yue - Catena, 2021 - Elsevier
Hyperspectral remote sensing technology has considerable research value in monitoring
and evaluating soil heavy metal pollution. In this study, the Three-River Source Region was …
and evaluating soil heavy metal pollution. In this study, the Three-River Source Region was …
Heavy metal contamination prediction using ensemble model: Case study of Bay sedimentation, Australia
Lead (Pb) is a primary toxic heavy metal (HM) which present throughout the entire
ecosystem. Some commonly observed challenges in HM (Pb) prediction using artificial …
ecosystem. Some commonly observed challenges in HM (Pb) prediction using artificial …
Data mining for pesticide decontamination using heterogeneous photocatalytic processes
Pesticides are chemical compounds used to kill pests and weeds. Due to their nature,
pesticides are potentially toxic to many organisms, including humans. Among the various …
pesticides are potentially toxic to many organisms, including humans. Among the various …
Digital exploration of selected heavy metals using Random Forest and a set of environmental covariates at the watershed scale
The current study was established for predicting some selected heavy metals (HMs)
including Zn, Mn, Fe, Co, Cr, Ni, and Cu, by applying random forest (RF) and a set of …
including Zn, Mn, Fe, Co, Cr, Ni, and Cu, by applying random forest (RF) and a set of …
[HTML][HTML] GNSS-R soil moisture retrieval based on a XGboost machine learning aided method: Performance and validation
Global navigation satellite system (GNSS)-reflectometry is a type of remote sensing
technology and can be applied to soil moisture retrieval. Until now, various GNSS-R soil …
technology and can be applied to soil moisture retrieval. Until now, various GNSS-R soil …
Monitoring of soil heavy metals based on hyperspectral remote sensing: A review
Y Wang, B Zou, L Chai, Z Lin, H Feng, Y Tang… - Earth-Science …, 2024 - Elsevier
Hyperspectral remote sensing (HRS) has emerged as a promising technique for monitoring
the spatiotemporal distribution of soil heavy metal (SHM) contamination, owing to its …
the spatiotemporal distribution of soil heavy metal (SHM) contamination, owing to its …
[HTML][HTML] Modeling and theoretical analysis of GNSS-R soil moisture retrieval based on the random forest and support vector machine learning approach
Global Navigation Satellite System-Reflectometry (GNSS-R) as a microwave remote sensing
technique can retrieve the Earth's surface parameters using the GNSS reflected signal from …
technique can retrieve the Earth's surface parameters using the GNSS reflected signal from …
[HTML][HTML] Estimation of heavy metals in agricultural soils using vis-NIR spectroscopy with fractional-order derivative and generalized regression neural network
X Xu, S Chen, L Ren, C Han, D Lv, Y Zhang, F Ai - Remote Sensing, 2021 - mdpi.com
With the development of industrialization and urbanization, heavy metal contamination in
agricultural soils tends to accumulate rapidly and harm human health. Visible and near …
agricultural soils tends to accumulate rapidly and harm human health. Visible and near …
Machine learning-based prediction of toxic metals concentration in an acid mine drainage environment, northern Tunisia
Abstract In northern Tunisia, Sidi Driss sulfide ore valorization had produced a large waste
amount. The long tailings exposure period and in situ minerals interactions produced an …
amount. The long tailings exposure period and in situ minerals interactions produced an …