An Intelligent Deep Learning Model for CO2 Adsorption Prediction
In this paper, we propose a supervised deep learning neural network (D-CNN) approach to predict CO2 adsorption form the textural and compositional features of biomass porous carbon waste and adsorption features. Both the textural and compositional features of biomass porous carbon waste are utilized...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2022-01-01
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| Series: | Adsorption Science & Technology |
| Online Access: | http://dx.doi.org/10.1155/2022/8136302 |
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