Research and application of data-driven carbon emission analysis and prediction
- Resource Type
- Conference
- Authors
- Wei, Dongmei; Meng, Dan
- Source
- 2023 2nd International Conference on Cloud Computing, Big Data Application and Software Engineering (CBASE) Cloud Computing, Big Data Application and Software Engineering (CBASE), 2023 2nd International Conference on. :157-160 Nov, 2023
- Subject
- Computing and Processing
Robotics and Control Systems
Signal Processing and Analysis
Analytical models
Economic indicators
Local government
Carbon dioxide
Predictive models
Market research
Software engineering
carbon emission
Carbon emission prediction
Machine learning
Neural network
Data Driven
- Language
The issue of carbon emissions has become an important policy direction for countries around the world to promote healthy socio-economic development and address climate change issues. This article conducts feature extraction and data analysis on various major energy data in China from 1997 to 2017, and constructs a model for verifying and predicting total carbon emissions. The model can not only accurately reflect China's carbon emissions over the past twenty years, but also predict future carbon emissions. This not only provides scientific basis for government decision-making, but also enriches the application of data-driven and artificial intelligence methods in this field.