AIMC Topic: Carbon

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Carbon price forecasting: a novel deep learning approach.

Environmental science and pollution research international
Carbon emission trading market promotes carbon emission reduction effectively. Accurate carbon price forecasting is crucial for relevant policy makers and investors. However, due to the non-linearity, uncertainty, and complexity of carbon prices, the...

Environmentally sustainable development and use of artificial intelligence in health care.

Bioethics
Artificial intelligence (AI) can transform health care by delivering medical services to underserved areas, while also filling gaps in health care provider availability. However, AI may also lead to patient harm due to fatal glitches in robotic surge...

Carbon Dot Blinking Fingerprint Uncovers Native Membrane Receptor Organizations via Deep Learning.

Analytical chemistry
Oligomeric organization of G protein-coupled receptors is proposed to regulate receptor signaling and function, yet rapid and precise identification of the oligomeric status especially for native receptors on a cell membrane remains an outstanding ch...

Water quality prediction model using Gaussian process regression based on deep learning for carbon neutrality in papermaking wastewater treatment system.

Environmental research
Wastewater recycling is the measure with enormous potentiality to achieve carbon neutrality in wastewater treatment plants. High-precision online monitoring can improve the stability of wastewater treatment system and help wastewater recycling. A new...

Deep learning approaches in remote sensing of soil organic carbon: a review of utility, challenges, and prospects.

Environmental monitoring and assessment
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...

Yield prediction of "Thermal-dissolution based carbon enrichment" treatment on biomass wastes through coupled model of artificial neural network and AdaBoost.

Bioresource technology
The "Thermal-dissolution based carbon enrichment" was proven as an efficient and homogenizing treatment method in converting biomass wastes into similar high-quality carbon materials. However, their yields varied significantly with respect to the dif...

Application of Various Machine Learning Techniques in Predicting Total Organic Carbon from Well Logs.

Computational intelligence and neuroscience
Unconventional resources have recently gained a lot of attention, and as a consequence, there has been an increase in research interest in predicting total organic carbon (TOC) as a crucial quality indicator. TOC is commonly measured experimentally; ...

Carbon price forecasting using multiscale nonlinear integration model coupled optimal feature reconstruction with biphasic deep learning.

Environmental science and pollution research international
Precise carbon price forecasting matters a lot for both regulators and investors. The improvement of carbon price forecasting can not only provide investors with rational advice but also make for energy conservation and emission reduction. But tradit...

Utilization of Artificial Neural Network in Predicting the Total Organic Carbon in Devonian Shale Using the Conventional Well Logs and the Spectral Gamma Ray.

Computational intelligence and neuroscience
Due to high oil and gas production and consumption, unconventional reservoirs attracted significant interest. Total organic carbon (TOC) is a significant measure of the quality of unconventional resources. Conventionally, TOC is measured experimental...

Determining soil particle-size distribution from infrared spectra using machine learning predictions: Methodology and modeling.

PloS one
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...