Research Article
Analysis of Factors Influencing Carbon Price Based on Graph Neural Network
@INPROCEEDINGS{10.4108/eai.19-5-2023.2334424, author={Di Huang and Chen Wang and Dengji Zhou and Jiarui Hao and Chongyuan Shui and Shixi Ma}, title={Analysis of Factors Influencing Carbon Price Based on Graph Neural Network}, proceedings={Proceedings of the 2nd International Conference on Bigdata Blockchain and Economy Management, ICBBEM 2023, May 19--21, 2023, Hangzhou, China}, publisher={EAI}, proceedings_a={ICBBEM}, year={2023}, month={7}, keywords={carbon market carbon price graph neural network transfer entropy influence analysis}, doi={10.4108/eai.19-5-2023.2334424} }- Di Huang
Chen Wang
Dengji Zhou
Jiarui Hao
Chongyuan Shui
Shixi Ma
Year: 2023
Analysis of Factors Influencing Carbon Price Based on Graph Neural Network
ICBBEM
EAI
DOI: 10.4108/eai.19-5-2023.2334424
Abstract
Due to greenhouse gas emissions caused by fossil energy use, it is urgent to reduce carbon emissions. The carbon market is a powerful tool for emission reduction, and the analysis of the relationship between carbon price and energy price is of great significance to the reasonable formulation of carbon price and the healthy operation of carbon market. Based on time convolutional network, transfer entropy matrix and graph attention network, the paper establishes a graph neural network model that can analyse the influencing factors of carbon price. Based on the data of carbon price, electricity price, natural gas price, oil price and temperature in China, the causal relationship and influence between carbon price and other factors are analysed, and the graph network structure with weights of carbon price and other factors is obtained.
