Prediction and analysis of the three major industries and residential consumption CO2 emissions based on least squares support vector machine in China
By Wei Sun, Mohan Liu. 2016
141 citations recorded by the source corpus.
Subfields: Economics and Econometrics, Environmental Engineering, Management Science and Operations Research
View Paper: https://www.semanticscholar.org/paper/bd59bcc226269828db5d1b71780af09aeabcde99
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In Economics and Econometrics
In Environmental Engineering
In Management Science and Operations Research
Citations in the corpus
- Forecasting Chinese carbon emissions from fossil energy consumption using non-linear grey multivariable models (2017, methodology): “Sun and Liu (2016) applied the least squares support vector machine (LSSVM) to predict different types of carbon dioxide emissions in China.”
- Short-term CO2 emissions forecasting based on decomposition approaches and its impact on electricity market scheduling (2020, background): “Apart from such CO2 intensity prediction methodologies, there are numerous research efforts and case studies [26, 27, 28, 29, 30, 31, 32] are discussing CO2 emissions predictions, which are closely related with CO2 intensity trend analysis.”