سامانه پشتیبانی خدمات اطلاعات

  اخبار و اعلانات

 آمار

تعداد نشریات162
تعداد شماره‌ها6,578
تعداد مقالات71,072
تعداد مشاهده مقاله125,683,123
تعداد دریافت فایل اصل مقاله98,912,700
Zangeneh Sirdari, Zahra, Ab. Ghani, Aminuddin, Zangeneh Sirdari, Nasim. (1393). Bedload transport predictions based on field measurement data by combination of artificial neural network and genetic programming. , 1(1), 85-94. doi: 10.7508/pj.2015.01.008
Zahra Zangeneh Sirdari; Aminuddin Ab. Ghani; Nasim Zangeneh Sirdari. "Bedload transport predictions based on field measurement data by combination of artificial neural network and genetic programming". , 1, 1, 1393, 85-94. doi: 10.7508/pj.2015.01.008
Zangeneh Sirdari, Zahra, Ab. Ghani, Aminuddin, Zangeneh Sirdari, Nasim. (1393). 'Bedload transport predictions based on field measurement data by combination of artificial neural network and genetic programming', , 1(1), pp. 85-94. doi: 10.7508/pj.2015.01.008
Zangeneh Sirdari, Zahra, Ab. Ghani, Aminuddin, Zangeneh Sirdari, Nasim. Bedload transport predictions based on field measurement data by combination of artificial neural network and genetic programming. , 1393; 1(1): 85-94. doi: 10.7508/pj.2015.01.008

Bedload transport predictions based on field measurement data by combination of artificial neural network and genetic programming

Pollution
مقاله 8، دوره 1، شماره 1، فروردین 2015، صفحه 85-94    اصل مقاله (639.61 K)
نوع مقاله: Original Research Paper
شناسه دیجیتال (DOI): 10.7508/pj.2015.01.008
نویسندگان
Zahra Zangeneh Sirdari* 1؛ Aminuddin Ab. Ghani1؛ Nasim Zangeneh Sirdari2
1REDAC, University of Sains Malaysia, Engineering Campus, 14300, NibongTebal, Penang, Malaysia
2Garmsar Branch, Islamic Azad University, Semnan, Iran
چکیده
Bedload transport is an essential component of river dynamics and estimation of its rate is important to many aspects of river management. In this study, measured bedload by Helley- Smith sampler was used to estimate the bedload transport of Kurau River in Malaysia. An artificial neural network, genetic programming and a combination of genetic programming and a neural network were used to estimate the bedload carried in Kurau River, based on bedload transport measurement data and hydraulic variables. A statistical analysis was carried out to validate methods by computing RMSE, MARE and inequality ratio (U). In general, the ability of the artificial neural network combined with genetic programming with R2 equal to 0.95, RMSE equal to 0.1 as a precipitation predictive tool for predicting the bedload transport rate was observed as being acceptable.
کلیدواژه‌ها
Artificial Neural Network؛ Bedload transport؛ Genetic programming؛ Kurau River
آمار
تعداد مشاهده مقاله: 3,046
تعداد دریافت فایل اصل مقاله: 2,159





سامانه مدیریت نشریات علمی. قدرت گرفته از سیناوب