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Computation of Evapotranspiration with Artificial Intelligence for Precision Water Resource Management
2020
Applied Sciences
Accurate estimation of reference evapotranspiration (ETo) provides useful information for water resource management and sustainable agriculture. This study estimates ETo with recurrent neural networks (RNNs), namely long short-term memory (LSTM) and bidirectional LSTM. Four representative meteorological sites (North Cape, Summerside, Harrington, and Saint Peters) were selected across Prince Edward Island (PEI), Canada to form a PEI dataset from mean values of the four sites' climatic variables
doi:10.3390/app10051621
fatcat:kgzu5grixvaydea3ppm5l6n3yq