Carbon Cycle

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Estimating regional effects of climate change and altered land use on biosphere carbon fluxes using distributed time delay neural networks with Bayesian regularized learning.

Neural networks : the official journal of the International Neural Network Society 30173057

The ability to accurately predict changes of the carbon and energy balance on a regional scale is of great importance for assessing the effect of land use changes on carbon sequestration under future climate conditions. Here, a suite of land cover-sp...

Atmosphere Bayes Theorem Carbon Carbon Cycle Climate Change Ecological Parameter Monitoring Machine Learning Models, Theoretical Neural Networks, Computer Oregon

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Soil carbon content prediction using multi-source data feature fusion of deep learning based on spectral and hyperspectral images.

Chemosphere 37302502

Visible near-infrared reflectance spectroscopy (VNIR) and hyperspectral images (HSI) have their respective advantages in soil carbon content prediction, and the effective fusion of VNIR and HSI is of great significance for improving the prediction ac...

Carbon Carbon Cycle Carbon Sequestration Deep Learning Soil

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Carbon Cycle

Estimating regional effects of climate change and altered land use on biosphere carbon fluxes using distributed time delay neural networks with Bayesian regularized learning.

Soil carbon content prediction using multi-source data feature fusion of deep learning based on spectral and hyperspectral images.

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