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• W4297898256 abstract "Excessive carbon dioxide emission leads to climate change and severely threaten social sustainability. A novel model for evaluating carbon dioxide emission in slurry shield tunneling is presented. Firstly, the carbon dioxide emission from a slurry shield tunnel during construction was calculated using the emission coefficient method. Then, for predicting carbon dioxide emission in slurry shield tunneling, a support vector regression integrated sparrow search algorithm model was proposed. Random forest is used to select the input variables of the model. The predicted model accuracy is validated by comparing it to multiple machine learning models. The results show that the model can accurately predict carbon dioxide emission in the shield tunneling with acceptable errors. The influencing factors for carbon dioxide emission in the slurry shield tunneling are disscussed. The recommendations for low-carbon tunnel construction are given. This study provides reference for guiding the low-carbon tunnel construction." @default.
• W4297898256 created "2022-10-01" @default.
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• W4297898256 date "2022-12-01" @default.
• W4297898256 modified "2023-09-30" @default.
• W4297898256 title "A novel evaluation model for carbon dioxide emission in the slurry shield tunnelling" @default.
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• W4297898256 doi "https://doi.org/10.1016/j.tust.2022.104757" @default.
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