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Deep Learning for Hydrometeorology and Environmental Science

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Deep Learning for Hydrometeorology and Environmental Science - Lee, Taesam, and Singh, Vijay P., and Cho, Kyung Hwa
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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. streamflow and temperature) and environmental science (e.g. water quality). Deep learning is known as part of machine learning methodology based on the artificial neural network. Increasing data availability and computing power enhance ...

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Deep Learning for Hydrometeorology and Environmental Science 2022, Springer Nature Switzerland AG, Cham

ISBN-13: 9783030647797

Paperback

Deep Learning for Hydrometeorology and Environmental Science 2021, Springer, Cham

ISBN-13: 9783030647766

2021 edition

Hardcover