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Deep Learning for Hydrometeorology and Environmental Science
part of the Water Science and Technology Library series
- Binding:
- Paperback
- Pages:
- 204
- Published:
- January 27, 2022
- Edition:
- 12021
- Dimensions:
- 155x235x0 mm.
- Weight:
- 343 g.
Delivery:
1-2 weeks
Expected delivery: January 4, 2025
Extended return policy to January 30, 2025
Description of Deep Learning for Hydrometeorology and Environmental Science
This book provides a step-by-step methodology and derivation of deep learning algorithms as Long Short-Term Memory (LSTM) and Convolution Neural Network (CNN), especially for estimating parameters, with back-propagation as well as examples with real datasets of hydrometeorology (e.g.
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