AIMC Topic: Soil

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Imputation by feature importance (IBFI): A methodology to envelop machine learning method for imputing missing patterns in time series data.

PloS one Jan 13, 2022
A new methodology, imputation by feature importance (IBFI), is studied that can be applied to any machine learning method to efficiently fill in any missing or irregularly sampled data. It applies to data missing completely at random (MCAR), missing ...
Algorithms Research Design Machine Learning Pakistan Radon Soil Time Factors
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Deep learning approaches in remote sensing of soil organic carbon: a review of utility, challenges, and prospects.

Environmental monitoring and assessment Nov 15, 2021
The use of neural network (NN) models for remote sensing (RS) retrieval of landscape biophysical and biochemical properties has become popular in the last decade. Recently, the emergence of "big data" that can be generated from remotely sensed data a...
Remote Sensing Technology Soil Deep Learning Environmental Monitoring Carbon
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Performing sequential forward selection and variational autoencoder techniques in soil classification based on laser-induced breakdown spectroscopy.

Analytical methods : advancing methods and applications Oct 28, 2021
The feasibility and accuracy of several combination classification models, , quadratic discriminant analysis (QDA), random forest (RF), Bernoulli naïve Bayes (BNB), and support vector machine (SVM) classification models combined with either sequentia...
Soil Spectrum Analysis Support Vector Machine Lasers Bayes Theorem
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DeepSense: A Physics-Guided Deep Learning Paradigm for Anomaly Detection in Soil Gas Data at Geologic CO Storage Sites.

Environmental science & technology Oct 25, 2021
Driven by the collection of enormous amounts of streaming data from sensors, and with the emergence of the internet of things, the need for developing robust detection techniques to identify data anomalies has increased recently. The algorithms for a...
Physics Prospective Studies Soil Deep Learning Carbon Dioxide
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Mapping high resolution National Soil Information Grids of China.

Science bulletin Oct 22, 2021
Soil spatial information has traditionally been presented as polygon maps at coarse scales. Solving global and local issues, including food security, water regulation, land degradation, and climate change requires higher quality, more consistent and ...
China Soil
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Predicting crop root concentration factors of organic contaminants with machine learning models.

Journal of hazardous materials Oct 5, 2021
Accurate prediction of uptake and accumulation of organic contaminants by crops from soils is essential to assessing human exposure via the food chain. However, traditional empirical or mechanistic models frequently show variable performance due to c...
Neural Networks, Computer Machine Learning Humans Linear Models Soil Crops, Agricultural
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Quantitative estimation of soil properties using hybrid features and RNN variants.

Chemosphere Aug 17, 2021
Estimating soil properties is important for maximizing the production of crops in sustainable agriculture. The hyperspectral data next input depends upon the previous one, and the current techniques do not take advantage of this sequential nature of ...
European Union Agriculture Sand Soil Neural Networks, Computer
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Robotic Assay for Drought (RoAD): an automated phenotyping system for brassinosteroid and drought responses.

The Plant journal : for cell and molecular biology Aug 10, 2021
Brassinosteroids (BRs) are a group of plant steroid hormones involved in regulating growth, development, and stress responses. Many components of the BR pathway have previously been identified and characterized. However, BR phenotyping experiments ar...
Arabidopsis Brassinosteroids Arabidopsis Proteins Seedlings Machine Learning Equipment Design Zea mays Triazoles Protein Kinases Image Processing, Computer-Assisted Phenotype Droughts Robotics Soil
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Prediction of soil-bearing capacity on forest roads by statistical approaches.

Environmental monitoring and assessment Jul 28, 2021
The soil-bearing capacity is one of the important criteria in dimensioning the superstructure. In Turkey, predictability of California Bearing Ratio values, which may be used in the planning and dimensioning of forest roads, of which about 26% lacks ...
Soil Environmental Monitoring Turkey Fuzzy Logic Forests
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Determining soil particle-size distribution from infrared spectra using machine learning predictions: Methodology and modeling.

PloS one Jul 20, 2021
Accuracy of infrared (IR) models to measure soil particle-size distribution (PSD) depends on soil preparation, methodology (sedimentation, laser), settling times and relevant soil features. Compositional soil data may require log ratio (ilr) transfor...
Particle Size Spectrophotometry, Infrared Soil Machine Learning Models, Theoretical Spectroscopy, Near-Infrared Carbon
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