JWSS - Journal of Water and Soil Science

In this study, the discharge coefficient of sharp-crested weirs located on circular channels was modeled using the ANFIS and ANFIS-Firefly (ANFIS-FA) algorithm. Also, the Monte Carlo simulations (MCs) were used to enhance the compatibilities of the soft computing models. However, the k-fold cross validation method (k=5) was used to validate the numerical models. According to the input parameters, four models of ANFIS and ANFIS-FA were introduced. Analyzing the numerical results showed that the superior model simulated the discharge coefficient as a function of the Froude number (Fr) and the ratio of flow depth over weir crest to the weir crest height) h/P(. The values of the mean absolute relative error (MARE), root mean square error (RMSE) and correlation coefficient (R) for the superior model were calculated 0.001, 0.002 and 0.999, respectively. However, the maximum error value for this study was less than 2%. 

Rainfall may be considered as the most important source of drinking water and watering land in different areas all over the world. Therefore, simulation and estimation of the hydrological phenomenon is of paramount importance. In this study, for the first time, the long-term rainfall in Rasht city was simulated using an optimum hybrid artificial intelligence (AI) model over a 62 year period from 1956 to 2017. The gene expression programming (GEP) and wavelet transform (WT) were combined to develop the hybrid AI model (WGEP). Firstly, the most effective lags of time series data were identified by means of the autocorrelation function (ACF); then eight various GEP and WGEP models were defined. Next, the GEP models were analyzed and the superior GEP model as well as the most influenced lags was detected. For instance, the variance accounting for (VAF), correlation coefficient (R) and scatter index (SI) for the superior GEP model was calculated to be 0.765, 0.508 and 0.709, respectively. Additionally, lags (t-1), (t-2), (t-3) and (t-12) were the most influenced. Then, the different mother wavelets were examined, indicating that the demy mother wavelet was the most optimal one. Moreover, analyzing the numerical simulations showed that the mother wavelet enhanced the performance of the GEP model significantly. For example, the VAF index for the superior WGEP model was increased almost three times after using the mother wavelet. Furthermore, the R and MARE statistical indices for the WGEP model were computed to be 0.935 and 0.862, respectively.