Domestic solid waste prediction with and enhanced LSTM with SigmoReLU and RAdam optimizer
A novel approach is presented to address the prediction challenge in domestic solid waste generation through the application of machine learning techniques. To overcome the limitations inherent in capturing intricate temporal patterns faced by conventional Long Short-Term Memory (LSTM) models design...
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| Main Authors: | , , , , , |
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| Format: | Conference or Workshop Item |
| Language: | en |
| Published: |
2024
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| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/11973/1/Domestic%20solid%20waste%20prediction%20with%20an%20enhanced%20LSTM%20with%20SigmoRELU%20and%20RAdam%20optimizer.pdf http://eprints.uthm.edu.my/11973/ https://doi.org/10.1007/978-3-031-66965-1_26 |
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