TY - JOUR ID - 63230 TI - Moldeling Of Dissolved Solids By Using Hybrid Soft Computing Methods (Case Study: Nazluchay Basin) JO - Iranian journal of Ecohydrology JA - IJE LA - en SN - 2423-6098 AU - Zamanzad Ghavidel, Sarvin AU - Montaseri, Majid AU - Sanikhani, Hadi AD - Ph.D Student, Water Resources Engineering, Urmia University AD - Assistant Professor, Department of Water Engineering, Urmia University AD - Assistant Professor, Department of Water Engineering, Kurdistan University Y1 - 2017 PY - 2017 VL - 4 IS - 4 SP - 983 EP - 996 KW - gene expression KW - Wavelet transform KW - Dissolved Solids KW - Nazluchay DO - 10.22059/ije.2017.63230 N2 - Rivers has important roles in providing drinking and agricultural water supply. In this study, single and hybrid-wavelet methods of artificial neural networks, adaptive neuro fuzzy inference system and Gene expression programming were validated total dissolved solids modelling of Nazluchay Basin. Therefore, water quality data with 19 years length (1993-2011), four hydrometric stations at Nazluchay Basin, were used. After validating of data and selected stations, the data were analyzed by using Daubechies-4 wavelet transform. For modelling 80% of data for training and 20% of data for testing of the model were used. The evaluation of models performance is applied based on different statistical tests, correlation coefficient, and mean root of error squares and mean absolute error. The results indicate acceptable performance of all single and hybrid-wavelet methods of artificial neural networks, adaptive neuro fuzzy inference system and Gene expression programming for modeling the total dissolved solids in the Nazluchay basin. Based on WGEP, GEP, WANFIS, ANFIS-SC, WANN, ANFIS-GP and ANN have best performance, respectively. In addition Gene expression programming-wavelet hybrid model with the minimum RMSE amounted 21.078 has best performance compared with other single and hybrid models. UR - https://ije.ut.ac.ir/article_63230.html L1 - https://ije.ut.ac.ir/article_63230_9387c8d63d2ec8a3a1cee33754103f49.pdf ER -