Predicting future global temperature and greenhouse gas emissions via LSTM model
Abstract This work is executed to predict the variation in global temperature and greenhouse gas (GHG) emissions resulting from climate change and global warming, taking into consideration the natural climate cycle. A mathematical model was developed using a Recurrent Neural Network (RNN) with Long–...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2023-12-01
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| Series: | Sustainable Energy Research |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s40807-023-00092-x |
