U + LSTM-F: A data-driven growth process model of rice seedlings
Accurately predicting the growth status of rice seedlings and understanding their growth rate and health status in a timely manner helps adjust the growth cycle and management measures. By predicting the growth status of the seedlings, the best time for transplanting can be selected, improving the s...
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| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-12-01
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| Series: | Ecological Informatics |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1574954124004643 |
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