Predicting River Flow Using an AI-Based Sequential Adaptive Neuro-Fuzzy Inference System

• Published in: Water
• Main Authors: Chiara Belvederesi, John A. Dominic, Quazi K. Hassan, Anil Gupta, Gopal Achari
• Format: Article in Journal/Newspaper
• Language: English
• Published: MDPI AG 2020
• Subjects: ANFIS; hydrological modeling; Athabasca River; water resources; predictive modeling; Hydraulic engineering; TC1-978; Water supply for domestic and industrial purposes; TD201-500; Canada; Nash; Sutcliffe
• Online Access: https://doi.org/10.3390/w12061622; https://doaj.org/article/b62b1e57ad9b4dc09dd5e32dca97df2a

Artificial intelligence (AI) techniques have been successfully adopted in predictive modeling to capture the nonlinearity of natural systems. The high seasonal variability of rivers in cold weather regions poses a challenge to river flow forecasting, which tends to be complex and data demanding. Thi...