Assessment of some famous empirical equation and artificial intelligent model (MLP, ANFIS) to predicting the side weir discharge coefficient

Message:
Article Type:
Research/Original Article (بدون رتبه معتبر)
Abstract:
Allocation and removing of excess water from the irrigation and drainage network is one of the most important activities in the management of these networks. Side weir is one of the most common structures for this purpose. Study on the flow Hydraulic characteristics of this structure included two parts, defining the water surface profiles and estimating the discharge coefficient. To estimate the discharge coefficient, many ways as experimental formulas and artificial intelligent models are propose. The empirical formula for simplifying in developing process that assume by the authors, contained significant error so using the AI models are inevitable. In this paper, some of the famous empirical formula and AI models such as Multilayer neural network (MLP) and Adaptive Neuro fuzzy inference system (ANFIS) are assessing with a laboratory experiment. Among the experimental formula, Borghei formula is most accurate (R2=0.83) and the performance of the AI model in Training and testing stage is more suitable (R2=0.96).
Language:
English
Published:
Journal of Applied Research in Water and Wastewater, Volume:1 Issue: 2, Summer and Autumn 2014
Pages:
74 to 79
magiran.com/p1886479  
دانلود و مطالعه متن این مقاله با یکی از روشهای زیر امکان پذیر است:
اشتراک شخصی
با عضویت و پرداخت آنلاین حق اشتراک یک‌ساله به مبلغ 1,390,000ريال می‌توانید 70 عنوان مطلب دانلود کنید!
اشتراک سازمانی
به کتابخانه دانشگاه یا محل کار خود پیشنهاد کنید تا اشتراک سازمانی این پایگاه را برای دسترسی نامحدود همه کاربران به متن مطالب تهیه نمایند!
توجه!
  • حق عضویت دریافتی صرف حمایت از نشریات عضو و نگهداری، تکمیل و توسعه مگیران می‌شود.
  • پرداخت حق اشتراک و دانلود مقالات اجازه بازنشر آن در سایر رسانه‌های چاپی و دیجیتال را به کاربر نمی‌دهد.
In order to view content subscription is required

Personal subscription
Subscribe magiran.com for 70 € euros via PayPal and download 70 articles during a year.
Organization subscription
Please contact us to subscribe your university or library for unlimited access!