کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6458563 1421108 2017 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Original papersPerformance investigation of the dam intake physical hydraulic model using Support Vector Machine with a discrete wavelet transform algorithm
ترجمه فارسی عنوان
مقالات اصلی بررسی کارآیی مدل هیدرولیکی فاضلاب با استفاده از دستگاه پشتیبانی بردار با الگوریتم تبدیل ویولت گسسته
کلمات کلیدی
از دست دادن سر، ساختار ورودی سد، پشتیبانی ماشین بردار الگوریتم موجک، عملکرد هیدرولیک،
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
چکیده انگلیسی


- Performance Assessment of a Dam Intake Structure.
- Optimal hydraulic design for the hydraulic-intake structure of dam.
- Effect of head losses and discharge capacity using a scaled down dam model.
- Support Vector Machine was designed and adapted.

In the present study hydraulic scaled model was conducted to evaluate an intake structure and checking its safety hydraulic performance. An investigation on the structural and mechanical equipment performance was performed by testing a scaled model to determine discharge capacity and head losses. In addition, the novel method established on Support Vector Machines (SVM) coupled through discrete wavelet transform was designed and adapted to estimate head loss at inlet and outlet section of the horizontal intake structure. Estimation and prediction results of SVM-WAVELET model was compared with genetic programming (GP) and artificial neural networks (ANNs) models. The model test results of SVM WAVELET approach reveal more accuracy in prediction and also attain improved generalization capabilities than GP and ANN. Furthermore, results specified that advanced SVM-WAVELET model can be applied confidently for auxiliary research to formulate predictive model for head loss at inlet and outlet section. Consequently, it was found that using of SVM-WAVELET is principally encouraging as an alternate strategy to predict the head loss as a representative of inner pressure head at intake structure.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers and Electronics in Agriculture - Volume 140, August 2017, Pages 48-57
نویسندگان
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