عنوان مقاله [English]
The aim of this study is to apply different methods to investigation the discharging capacity of a sharp-crested curved plan-form weirs through the Adaptive neuro fuzzy inference system (ANFIS) and Support Vector Machines (SVM) techniques. Subsequently, For training and testing of the proposed equation, experimental data of Kumar et al, have been used and prediction of discharge coefficient through the ANFIS and SVM were compared with equations were proposed with Kumar et al and Zahiri. The result showe that proposed artificial inteligince models have sutable accuracy and also result of superior models is related to total upstream head, spillway height and the angle of curvature of axis curve which demonstrate direct relationship between discharge coefficient and hydraulic properties. Moreover, the performance of ANFIS model is a bit better than SVM technique with relatively low error and high correlation values. Determination coefficient of the proposed equation for discharge coefficient have been calculated as 0.993 for the ANFIS model with Hybrid training method and two point Gaussian membership function, Also this parameter calculated for SVM with RBF Kernel type and with having values include 3, 10 and 0.1 that is related to γ,c and ε respectively as 0.98 for testing phases
ظهیری،ع. 1394. استخراج رابطه ضریب دبی در سرریزهای قوسی به کمک شبکه برنامهریزی ژنتیک، نشریه آبیاری و زهکشی ایران. 2.9: 323-334.
ASCE Task Committee on Application of Artificial Neural Networks in Hydrology. 2000a. Artificial Neural Networks in hydrology. I: Preliminary concepts. Journal of Hydrologic Engineering. ASCE. 5.2: 115-123.
Asthana,K.C., Syed Tahir,H and Syed,Y. 1961. Flow over curved weirs. Water and Energy International. 18.8: 744-761.
Chen,Q., Dai,G., Liu,H. 2002. Volume of Fluid Model for Turbulence Numerical Simulation of Stepped Spillway Overflow. Journal of hydraulic engineering. 128.7:683-688.
Cortes,C and Vapnik,V. 1995. Support-vector networks, Machine Learning. 20.3: 273.
Jang,J.S.R. 1993. ANFIS: Adaptive-Network Based fuzzy inference system. IEEE Tran's system, Man, Cybernetic. 23.3: 665-685.
Khan,M.S and Coulibaly,P. 2006. Application of Support Vector Machine in ake Water Level Prediction. Journal of Hydrologic Engineering. 11.3: 199-205.
Kindsvater,C.E and Carter,R.W. 1959. Discharge characteristics of rectangular thin-plate weirs. Transactions, American Society of Civil Engineers. 124.1:772-801.
Kisi,O. 2007. The potential of different ANN techniques in evapotranspiration modeling. Journal of Hydrological Process. 22.14: 2449-2460.
Kumar,S., Ahmad,Z., Mansoor,T., Himanshu,S.K. 2012. Discharge Characteristics of Sharp Crested Weir of Curved Plan-form. Research Journal of Engineering Sciences. 1.4: 16-20.
Lee,W and Hoops,J.A. 1996. Prediction of Cavitation Damage for Spillways. Journal of Hydraulic Engineering. 122.9: 481-488.
Liong,S.Y., Gautam,T.R., Khu,S.T., Babovic,V., Keijzer,M., Muttil,N. 2002. Genetic programming, A new paradigm in rainfall runoff modeling. JAWRA Journal of the American Water Resources Association. 38.3: 705-718.
Lohani,A.K., Goel,N.K and Bhatia,K.K.S. 2007 Deriving stage–discharge–sediment concentration relationships using fuzzy logic. Hydrological Sciences Journal.52.4:793-807.
Nourani,V., Kisi,O., Komasi,M. 2011. Two hybrid Artificial Intelligence approaches for modeling rainfall-runoff process. Journal of Hydrology. 402.1-2:41-59.
Roushangar,K and Alizadeh,F. 2015. Suitability of different modelling strategies in predicting of solid load discharge of an alluvial river. 36th world congress of IAHR. 1-10.
Roushangar,K., Vojoudi,F and Shiri,J. 2014. Modeling river total bed material load discharge using artificial intelligence approaches (based on conceptual inputs). Journal of Hydrology. 514: 114-122.
Saneie,M., SheikhKazemi,J., Azhdary Moghaddam,M. 2016. Scale Effects on the Discharge Coefficient of Ogee Spillway with an Arc in Plan and Converging Training Walls, Civil Engineering Infrastructures Journal. 49.2: 361-374
Swamee,P.K., Shekhar,C.H., Talib,M. 2011. Discharge characteristics of skew weirs” Journal of Hydraulic Research. 49.6: 818-820.