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International Journal of Engineering، جلد ۲۶، شماره ۲، صفحات ۱۷۷-۱۸۶
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عنوان فارسی |
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چکیده فارسی مقاله |
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کلیدواژههای فارسی مقاله |
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عنوان انگلیسی |
An ANFIS-based Approach for Predicting the Manning Roughness Coefficient in Alluvial Channels at the Bank-full Stage |
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چکیده انگلیسی مقاله |
An intelligent method based on adaptive neuro-fuzzy inference system (ANFIS) for identifying Manning’s roughness coefficients in modeling of alluvial river is presented. The procedure for selecting values of Manning n is subjective and requires judgment and skill which are developed primarily through experience. During practical applications, researchers often find that a correct choice of the Manning n can be crucial to make a sound prediction of hydraulic problems. In this paper, an ANFIS model was set up to predict the Manning coefficient of alluvial river, with the mean bed particle size, mean flow depth and channel slope as three input parameters. The regression equations are also applied to the same data. Statistic measures were used to evaluate the performance of the models. Based on comparison of the results, it is found that the ANFIS model gives better estimates than the other empirical relationships. Also, a sensitivity analysis showed that mean flow depth has a greater influence on Manning coefficient than the other independent parameters in ANFIS model. |
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کلیدواژههای انگلیسی مقاله |
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نویسندگان مقاله |
Mirali Mohammadi | Civil Engineering, Urmia University
amir bahramifar | Engineering Faculty, Urmia University
Reza Shirkhani | Civil Engineering, Pars Special Econemic Energy Zon
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نشانی اینترنتی |
http://www.ije.ir/article_72085_19af70835133ad8ce93d184baa433bc6.pdf |
فایل مقاله |
اشکال در دسترسی به فایل - ./files/site1/rds_journals/409/article-409-2062953.pdf |
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زبان مقاله منتشر شده |
en |
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نوع مقاله منتشر شده |
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