Carbon emission combined prediction of main ports in China based on variational modal decomposition

CHEN Zhefeng; WANG Jian

doi:10.3969/j.issn.1000-4653.2024.04.018

Navigation of China > 2024 > 47(4): 138-145. > DOI: 10.3969/j.issn.1000-4653.2024.04.018

CHEN Zhefeng, WANG Jian. Carbon emission combined prediction of main ports in China based on variational modal decomposition[J]. Navigation of China, 2024, 47(4): 138-145. DOI: 10.3969/j.issn.1000-4653.2024.04.018

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Carbon emission combined prediction of main ports in China based on variational modal decomposition

CHEN Zhefeng,
WANG Jian^,

School of Economics and Management, Fuzhou University, Fuzhou 350108, China

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Received Date: June 20, 2023

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Abstract

As a major energy-consuming and greenhouse gas emitter,the study of carbon emission trends in ports is crucial for promoting the construction of green and ecological ports in China.Considering the multi-scale characteristics of port carbon emission fluctuations,this paper takes the major container ports in China as the objects,and constructs a multi-scale combined forecasting model integrating Variational Modal Decomposition-Wavelet Neural Network-Genetic Algorithm-Back Propagation Neural Network（VMD-WNN-GA-BPNN）.Based on the idea of decomposition-subsequence forecastingensemble forecasting,the carbon emissions series are decomposed into multiple modal components by using VMD.The components are classified into low,medium and high frequency and trend terms according to their fluctuation characteristics,then,this paper optimizes forecast method respectively to achieve itemized forecast,and completes an integrated forecast and analyzes the effect of the forecast using the sub-predicted values.Example applications show that,compared with the existing prediction models,the multi-scale combined prediction model constructed in the paper can significantly improve the prediction accuracy of port carbon emissions and reveal the intrinsic multi-scale characteristics of port carbon emissions,which is conducive to the formulation of targeted carbon emission reduction strategies from the scales of energy technologies,seasons,and emergencies.
- container port,
- carbon emission prediction,
- variational modal decomposition,
- multi-scale combined forecasting model

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