An ANFIS-based Approach for Predicting the Manning Roughness Coefficient in Alluvial Channels at the Bank-full Stage

سال انتشار: 1391
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 978

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شناسه ملی سند علمی:

JR_IJE-26-2_010

تاریخ نمایه سازی: 17 خرداد 1393

چکیده مقاله:

An intelligent method based on adaptive neuro-fuzzy inference system (ANFIS) for identifying Manning’s roughness coefficient, n, in modeling of alluvial channels e.g. rivers is presented. Theprocedure for selecting values of the Manning n is subjective and requires engineering judgments andskills developed primarily through experience. During practical applications, researchers often find thata correct choice of the Manning n can be crucial to make a sound prediction of hydraulic problems. Inthis paper, an ANFIS model is set up to predict the Manning coefficient of river channels, with the mean bed particle size, mean flow depth and channel bed slope, as some three input parameters. The regression equations are also applied to the same data. Statistic measures are then used to evaluate theperformance of the models. Based on the comparison of the results, it is well found that the ANFISmodel presented here gives some better estimates than the other empirical relationships. Also, a sensitivity analysis showed that mean flow depth has a greater influence on the Manning coefficient than the other independent parameters in ANFIS model.

نویسندگان

a bahramifar

Department of Civil Engineering, Faculty of Engineering, Urmia University, PO Box ۱۶۵, Urmia ۵۷۵۶۱-۱۵۳۱۱, Iran

r Shirkhani

Expert of civil engineering, Pars Oil and Gas Company (P.O.G.C), Phase ۱۳, Pars Special Econemic Energy Zone, Asaluye, Iran

m Mohammadi

Department of Civil Engineering, Faculty of Engineering, PO Box ۱۶۵, Urmia ۵۷۵۶۱-۱۵۳۱۱, Iran