Application of wavelet-artificial intelligence hybrid models for water quality prediction: a case study in Aji-Chay River, Iran

• Published in: Stochastic environmental research and risk assessment Vol. 30; no. 7; pp. 1797 - 1819
• Main Authors: Barzegar, Rahim, Adamowski, Jan, Moghaddam, Asghar Asghari
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.10.2016; Springer Nature B.V
• Subjects: Adaptive systems; Aquatic Pollution; Artificial intelligence; Artificial neural networks; Chemistry and Earth Sciences; Computational Intelligence; Computer Science; Earth and Environmental Science; Earth Sciences; Environment; Freshwater; Learning theory; Math. Appl. in Environmental Science; Mathematical models; Neural networks; Original Paper; Parameters; Physics; Probability Theory and Stochastic Processes; Rivers; Salinity; Statistical analysis; Statistics for Engineering; Waste Water Technology; Water Management; Water Pollution Control; Water quality; Wavelet; Wavelet transforms; China; ISW, Iran; Water quality prediction; Discrete wavelet transform; Iran; Aji-Chay River; Artificial intelligence models

The accuracy of Artificial Neural Network (ANN), Adaptive Neuro-Fuzzy Inference System (ANFIS), wavelet-ANN and wavelet-ANFIS in predicting monthly water salinity levels of northwest Iran’s Aji-Chay River was assessed. The models were calibrated, validated and tested using different subsets of month...