@article{1433593,
      author = {Lee, Taesam, and Singh, V. P. and Cho, Kyung Hwa,},
      url = {http://library.usi.edu/record/1433593},
      title = {Deep learning for hydrometerology and environmental  science /},
      abstract = {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).},
      doi = {https://doi.org/10.1007/978-3-030-64777-3},
      recid = {1433593},
      pages = {1 online resource},
}