ARTIFICIAL NEURAL NETWORKS IN HYDROLOGY: II, HYDROLOGIC APPLICATIONS

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Adaptive neuro-fuzzy inference system for prediction of water level in reservoir (2006, methodology): “The ASCE Task Committee report [40] [41] did a comprehensive review of the application of ANNs to hydrology, as did Maier and Dandy [27], and also Govindaraju and Rao [14] in a specialized publication.”
Data-Based Models for the Prediction of Dam Behaviour: A Review and Some Methodological Considerations (2017, background): “9] to avoid the above mentioned problems [40], [5], [41].”
Application of the extreme learning machine algorithm for the prediction of monthly Effective Drought Index in eastern Australia (2015, unknown): “ANN is a powerful and versatile data-driven algorithm for capturing and representing complex input and output relationships (Abbot and Marohasy, 2012, 2014; Govindaraju, 2000; Şahin et al., 2013).”