AIMC Topic: Soil
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Downscaling satellite soil moisture using geomorphometry and machine learning.
PloS one
Sep 24, 2019
Annual soil moisture estimates are useful to characterize trends in the climate system, in the capacity of soils to retain water and for predicting land and atmosphere interactions. The main source of soil moisture spatial information across large ar...
Valuation methodology of laminar erosion potential using fuzzy inference systems in a Brazilian savanna.
Environmental monitoring and assessment
Sep 7, 2019
This study presents an approach on the evaluation of potential laminar erosion in the Ribeirão Sucuri Grande watershed. It is located in the northeast of the state of Goiás, Brazil, a conservation area under strong anthropogenic pressure. A Mamdani f...
Modelling and Optimizing Pyrene Removal from the Soil by Phytoremediation using Response Surface Methodology, Artificial Neural Networks, and Genetic Algorithm.
Chemosphere
Jul 30, 2019
This study aimed to model and optimize pyrene removal from the soil contaminated by sorghum bicolor plant using Response Surface Methodology (RSM) and Artificial Neural Network (ANN) with Genetic Algorithm (GA) approach. Here, the effects of indole a...
Artificial Neural Networks (ANNs) and Response Surface Methodology (RSM) Approach for Modelling the Optimization of Chromium (VI) Reduction by Newly Isolated Strain NS-MIE from Agricultural Soil.
BioMed research international
May 26, 2019
Numerous technologies and approaches have been used in the past few decades to remove hexavalent chromium (Cr[VI]) in wastewater and the environment. However, these conventional technologies are not economical and efficient in removing Cr(VI) at a ve...
Research on soil moisture prediction model based on deep learning.
PloS one
Apr 3, 2019
Soil moisture is one of the main factors in agricultural production and hydrological cycles, and its precise prediction is important for the rational use and management of water resources. However, soil moisture involves complex structural characteri...
Automated anomalous behaviour detection in soil radon gas prior to earthquakes using computational intelligence techniques.
Journal of environmental radioactivity
Mar 9, 2019
In this article, three computational intelligence (CI) models were developed to automatically detect anomalous behaviour in soil radon gas (Rn) time series data. Data were obtained at a fault line and analysed using three machine learning techniques ...
Using artificial neural network to investigate physiological changes and cerium oxide nanoparticles and cadmium uptake by Brassica napus plants.
Environmental pollution (Barking, Essex : 1987)
Dec 12, 2018
Heavy metals and emerging engineered nanoparticles (ENPs) are two current environmental concerns that have attracted considerable attention. Cerium oxide nanoparticles (CeONPs) are now used in a plethora of industrial products, while cadmium (Cd) is ...
The latitudinal gradient in rock-inhabiting bacterial community compositions in Victoria Land, Antarctica.
The Science of the total environment
Dec 6, 2018
The harsh conditions in Victoria Land, Antarctica have formed a simple ecosystem dominated by microbes that use rocks as shelters to avoid environmental stressors. The area is composed of basement rocks that illustrate the history of complex deformat...
Forecasting the spatiotemporal variability of soil CO emissions in sugarcane areas in southeastern Brazil using artificial neural networks.
Environmental monitoring and assessment
Nov 21, 2018
Carbon dioxide (CO) is considered one of the main greenhouse effect gases and contributes significantly to global climate change. In Brazil, the agricultural areas offer an opportunity to mitigate this effect, especially with the sugarcane crop, sinc...
A novel method for predicting cadmium concentration in rice grain using genetic algorithm and back-propagation neural network based on soil properties.
Environmental science and pollution research international
Oct 24, 2018
Heavy metal pollution is a global ecological safety issue, especially in crops, where it directly threatens regional ecological security and human health. In this study, the back-propagation (BP) neural network optimized by the genetic algorithm (GA)...
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