کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1726611 | 1520755 | 2011 | 6 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Linear genetic programming to scour below submerged pipeline
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
مهندسی دریا (اقیانوس)
پیش نمایش صفحه اول مقاله

چکیده انگلیسی
Genetic programming (GP) has nowadays attracted the attention of researchers in the prediction of hydraulic data. This study presents Linear Genetic Programming (LGP), which is an extension to GP, as an alternative tool in the prediction of scour depth below a pipeline. The data sets of laboratory measurements were collected from published literature and were used to develop LGP models. The proposed LGP models were compared with adaptive neuro-fuzzy inference system (ANFIS) model results. The predictions of LGP were observed to be in good agreement with measured data, and quite better than ANFIS and regression-based equation of scour depth at submerged pipeline.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Ocean Engineering - Volume 38, Issues 8â9, June 2011, Pages 995-1000
Journal: Ocean Engineering - Volume 38, Issues 8â9, June 2011, Pages 995-1000
نویسندگان
H.Md. Azamathulla, Aytac Guven, Yusuf Kagan Demir,