| Title |
Prediction method of green transportation carbon emission in smart city based on gray joint algorithm |
| ID_Doc |
36225 |
| Authors |
Gao, RZ; Li, X; Yu, HT |
| Title |
Prediction method of green transportation carbon emission in smart city based on gray joint algorithm |
| Year |
2021 |
| Published |
|
| DOI |
10.1109/ICSGEA53208.2021.00015 |
| Abstract |
In order to improve the accuracy and efficiency of green transportation carbon emission prediction in smart city, this paper proposes a new green transportation carbon emission prediction method based on gray joint algorithm. This method first analyzes the factors that affect the green transportation carbon emission of smart city, and selects the carbon emission intensity and urban energy efficiency as the key factors to calculate. Based on the calculation results, support vector machine is used to solve the linear prediction problem of traffic carbon emissions. The result of support vector regression is regarded as gray value, and the gray value fitting calculation is completed by using accumulation method. Based on the gray value calculation results, combined with the residual calculation results, the gray prediction model of carbon emission is constructed, and the prediction of green transportation carbon emission in smart city is significantly improved. |
| Author Keywords |
gray level combination algorithm; smart city; green traffic; carbon emission prediction |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Conference Proceedings Citation Index - Science (CPCI-S) |
| EID |
WOS:000851388300007 |
| WoS Category |
|
| Research Area |
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| PDF |
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