Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Carbonation Shrinkage01:24

Carbonation Shrinkage

182
Atmospheric CO2 penetrates the concrete's pores and, in the presence of moisture, forms carbonic acid, which then reacts with calcium hydroxide in the hydrated cement, forming calcium carbonate. This process reduces the concrete's volume and is termed carbonation shrinkage.
The concrete's permeability is slightly reduced as calcium carbonate produced during the reaction fills its pores. Furthermore, its strength is slightly enhanced as the water released during the reaction...
182
Shrinkage in Concrete01:27

Shrinkage in Concrete

143
Shrinkage in concrete is primarily due to water loss from evaporation, hydration of cement, or carbonation, leading to a reduction in volume. The volumetric contraction results in volumetric strain in concrete. However, in practice, shrinkage is measured as linear strain, which is one-third of the volumetric strain.
When concrete is still in its plastic state, it can undergo a decrease in volume by about 1% of its absolute volume. This decrease is known as plastic shrinkage. It arises either...
143
Drying Shrinkage01:21

Drying Shrinkage

120
When hardened concrete is exposed to air with a relative humidity of less than 100 percent, it begins to lose the free water within its capillaries. As this water evaporates, the water initially adsorbed onto the calcium silicate hydrates migrates towards these now empty spaces and eventually evaporates as well. Over time, as more water leaves, the volume of the concrete decreases, a phenomenon known as drying shrinkage.
A portion of this drying shrinkage can be reversed; if the concrete is...
120
Regression Analysis01:11

Regression Analysis

5.9K
Regression analysis is a statistical tool that describes a mathematical relationship between a dependent variable and one or more independent variables.
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
5.9K
Residual Plots01:07

Residual Plots

5.0K
A residual plot is a statistical representation of data used to analyze correlation and regression results. It helps verify the requirements for drawing specific conclusions about correlation and regression. To obtain the residual plot, first, the residual for each data value is calculated, which is simply the vertical distance between the observed and the predicted value obtained from the regression equation.
When the residual values are plotted against the variable x, it is called a residual...
5.0K
Estimation of the Physical Quantities01:05

Estimation of the Physical Quantities

4.6K
On many occasions, physicists, other scientists, and engineers need to make estimates of a particular quantity. These are sometimes referred to as guesstimates, order-of-magnitude approximations, back-of-the-envelope calculations, or Fermi calculations. The physicist Enrico Fermi was famous for his ability to estimate various kinds of data with surprising precision. Estimating does not mean guessing a number or a formula at random. Instead, estimation means using prior experience and sound...
4.6K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Forecasting crude oil futures price with energy uncertainty: Evidence from machine learning methods.

PloS one·2026
Same author

Carbon price prediction based on a scaled PCA approach.

PloS one·2024
Same author

Stock index trend prediction based on TabNet feature selection and long short-term memory.

PloS one·2022
See all related articles

Related Experiment Video

Updated: Aug 13, 2025

Measurements of CO2 Fluxes at Non-Ideal Eddy Covariance Sites
09:05

Measurements of CO2 Fluxes at Non-Ideal Eddy Covariance Sites

Published on: June 24, 2019

8.0K

Forecasting Carbon Price Using Double Shrinkage Methods.

Xiaolu Wei1, Hongbing Ouyang2

  • 1Business School, Hubei University, Wuhan 430062, China.

International Journal of Environmental Research and Public Health
|January 21, 2023
PubMed
Summary

Accurate carbon price forecasting is crucial for carbon trading markets. This study introduces a novel double shrinkage method, outperforming existing models in prediction accuracy and robustness for complex time series analysis.

Keywords:
carbon price forecastingdimensionality reductiondouble shrinkage methodsfactor screening

More Related Videos

Measuring Carbon-based Contaminant Mineralization Using Combined CO2 Flux and Radiocarbon Analyses
11:19

Measuring Carbon-based Contaminant Mineralization Using Combined CO2 Flux and Radiocarbon Analyses

Published on: October 21, 2016

12.0K
Split Point Analysis and Uncertainty Quantification of Thermal-Optical Organic/Elemental Carbon Measurements
10:22

Split Point Analysis and Uncertainty Quantification of Thermal-Optical Organic/Elemental Carbon Measurements

Published on: September 7, 2019

8.3K

Related Experiment Videos

Last Updated: Aug 13, 2025

Measurements of CO2 Fluxes at Non-Ideal Eddy Covariance Sites
09:05

Measurements of CO2 Fluxes at Non-Ideal Eddy Covariance Sites

Published on: June 24, 2019

8.0K
Measuring Carbon-based Contaminant Mineralization Using Combined CO2 Flux and Radiocarbon Analyses
11:19

Measuring Carbon-based Contaminant Mineralization Using Combined CO2 Flux and Radiocarbon Analyses

Published on: October 21, 2016

12.0K
Split Point Analysis and Uncertainty Quantification of Thermal-Optical Organic/Elemental Carbon Measurements
10:22

Split Point Analysis and Uncertainty Quantification of Thermal-Optical Organic/Elemental Carbon Measurements

Published on: September 7, 2019

8.3K

Area of Science:

  • Environmental Economics
  • Econometrics
  • Data Science

Background:

  • Accurate carbon price forecasting is vital for effective carbon trading market development.
  • Existing prediction models face challenges with complex, non-linear time series data.

Purpose of the Study:

  • To propose and evaluate a hybrid carbon price prediction model using double shrinkage methods.
  • To enhance the accuracy and robustness of carbon price forecasting.

Main Methods:

  • A hybrid model combining factor screening, dimensionality reduction, and prediction.
  • Empirical analysis using data from the Guangdong carbon trading market (August 2013 - March 2022).
  • Comparison with alternative models using R², RMSE, and RAE metrics.

Main Results:

  • The proposed double shrinkage methods significantly improve prediction accuracy over alternative models.
  • LSTM-based double shrinkage methods demonstrate superior performance compared to LR-based methods.
  • Findings remain robust across various data normalization, frequency, market, and dataset division scenarios.

Conclusions:

  • The double shrinkage method offers a more accurate and reliable approach to carbon price prediction.
  • This study contributes novel insights for analyzing complex, non-linear time series in environmental markets.
  • The findings have potential theoretical and practical implications for carbon trading market management.