Side weir is a type of weirs that used extensively in a variety ofengineering projects such as river engineering, dam,waste water , Irrigation and drainage network. So the study on the flow characteristics on the type weir, is one of the mostimportant topics in hydraulic engineering. The spatially varied flow (S.V.F)with discharge decreasing is governing equation to this type weir.Study on the hydraulic characteristics of this Structural, divided two part. One calculation of water surface profiles and twoestimate the discharge coefficient estimate. Numerical methods used to modeling water surface profiles. And for estimating of discharge coefficient the empirical equation and intelligent method proposed.In this study a numerical model (Fourth-Order Runge–Kutta Method)has been presented for solving spatially varied flow(S.V.F) and follow evaloution of empirical equation has done then to estimate of discharge coefficient the MLP model has been implement. For developting the ANFIS model,the data that poblished in journal has been used. The final result has good agreement with experimental data and can accurately simulate the flow over side weir. تفاصيل المقالة

Reductionof Surface water quality and pollution in the environment is majorproblems. This issuewill become more important because the rivers are as a source for supplied for drinking water forpeople, industrial and agriculture. Prediction and modeling of hydraulic phenomenon is one of themost importantactivities of Hydraulic Engineering. Neural network is one of the most usefulmethods of data processing which capable of modeling the complex relationships between inputand output. In this study, for prediction of the dispersion coefficient of pollution in rivers andthedevelopment of neural network (ANN) and empirical formulas wasstudied. Best accuracy ofthem is related to the Tavakollizadeh and Kashefipur, formula which its error index R 2 􀀠 0.77 .To increase in the perdition of the dispersion coefficient, the multi-layer perceptron (MLP) wasdeveloped. Training process and simulation MLP model was conducted in the Matlabsoftwareenvironment.To increase the performance of the MLP, genetic algorithm for training process isused. The results showed that the MLP are more accurate in comparison with otherempiricalequations.Using genetic algorithms for neural network training the neural networkmodel will further increase its accuracy about the 19 percent. تفاصيل المقالة

Study in surface water quality is important. Rivers are one of the main sources of water supply fordrinking, agriculture and industry. Unfortunately, sometime Rivers where wastewater dischargesare considered. For this reason,the pollutant transmission in river is one of the most importantproblems in Environmental Engineering. the Advection Dispersion Equation (ADE) is governedon the pollutant transport in river. this equation is partial differential equation (PDE). Thisequation is used most widely in fluid engineering spatially water engineering and in generalnamed convection equation.to Preparate computer programs that can simulate the pollutanttransmission, in addition to the used numerical method to solution of the convection equation ,thecalculation of Longitudinal Dispersion coefficient (LDC) is needed. Many empirical formulas arepresented for calculating the LDC. the assessment of this equations shows that Most of theiraccuracy is not satisfactory. Thus the use of Artificial Intelligent techniques is inevitable. In thispaper, the finite volume method is used discretiz of ADE and to estimate the diffusion coefficient,adaptive neural network (ANFIS) has been developed. the result of ANFIS model shows that Theaccuracy and performance of the model in training and testing process is very suitable. After thedevelopment of an artificial intelligence model general model was developed. the result of thefinal model tested with analytical solution of ADE and observation data of the Severn River in theUK. the final result show that performance of model is suitable.Keywords: transmission of pollutant, finite volume method, Severn river تفاصيل المقالة