دانلود مقاله ISI انگلیسی شماره 110387
ترجمه فارسی عنوان مقاله

پیش بینی ضریب تخلیه لرزه ای مثلثی با استفاده از رگرسیون برداری حمایت، رگرسیون فشرده برداری، روش پاسخ سطوح و تجزیه و تحلیل مولفه های اصلی

عنوان انگلیسی
Predicting discharge coefficient of triangular labyrinth weir using Support Vector Regression, Support Vector Regression-firefly, Response Surface Methodology and Principal Component Analysis
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
110387 2017 22 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Flow Measurement and Instrumentation, Volume 55, June 2017, Pages 75-81

پیش نمایش مقاله
پیش نمایش مقاله  پیش بینی ضریب تخلیه لرزه ای مثلثی با استفاده از رگرسیون برداری حمایت، رگرسیون فشرده برداری، روش پاسخ سطوح و تجزیه و تحلیل مولفه های اصلی

چکیده انگلیسی

Weirs are hydraulic structures which conduct the most powerful flow with large overflow. Discharge flow predication is based on capacity discharge designation by designer. In this paper, the discharge capacity in triangular labyrinth side-weirs is computed by using new techniques with high precision. The four employed techniques for computation of discharge capacity are: Support Vector Regression (SVR), Support Vector Regression–Firefly (SVR- Firefly), Response Surface Methodology (RSM) and Principal Component Analysis (PCA). A comparison between the computed discharge capacity and empirical results is considered in this paper. Determination coefficient (R2), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), SI and δ are five statistical indicators which help us to measure the precision of the designed models. The statistical indices indicated that the SVR-Firefly model has the highest ability among the models for simulation, with average MAPE=0.49%, R2=0.991 and RMSE=0.0035. Like the results achieved by the SVR-Firefly, comparatively good results were obtained by both PCA and SVR models. The SVR model suggested the average MAPE value near 1.073 in the training mode under the most unfavorable conditions. The MAPE value equal to 1.23 was also obtained in the test mode. This proves that the value of error rate is tolerable.