پديد آورنده :
آقاجان عبدالله، مسعود
عنوان :
كاربرد مدل هاي شبكه عصبي و عصبي- فازي تطبيقي در تعيين ضريب تخليه جريان سر ريزهاي كناري Discharge Coefficient of Side WeirsT Using Neural- Net works and ANFIS Models
مقطع تحصيلي :
كارشناسي ارشد
محل تحصيل :
اصفهان: دانشگاه صنعتي اصفهان، دانشكده عمران
صفحه شمار :
نوزده،112ص.: مصور،جدول،نمودار
يادداشت :
ص.ع.به فارسي و انگليسي
استاد راهنما :
عبدالرضا كبيري ساماني، رضا حجازي طاقانكي
استاد مشاور :
محمود برقعي
توصيفگر ها :
سرريز كناري لبه تيز , سرريز كناري منقاري
تاريخ نمايه سازي :
3/7/89
استاد داور :
مريم ذكري، حميدرضا صفوي
چكيده فارسي :
به فارسي و انگليسي: قابل رويت در نسخه ديجيتالي
چكيده انگليسي :
Isfahan University of Technology Department of Civil Engineering Discharge Coefficient of Side Weirs Using Neural Networks and ANFIS Models By Masoud Aghajan Supervisors Abdorreza Kabiri Samani Seyyed Reza Hejazi Taghanaki Abstract Side weirs are flow regulating devices commonly encountered in hydraulic engineering A side weir is an over flow weir framed in the side of a channel over which lateral outflow takes place when the water surface in the channel rises above the weir crest They are widely used for flow diversion in irrigation drainage urban sewage systems and also in intake structures It is essential to correctly predict the weir discharge coefficient for hydraulic engineers regarding to the technical and economical design of side weirs Although the discharge coefficient for flow over side weirs was investigated experimentally by many investigators but an overall acceptable formula or a complete analytical solution of the equation governing the flow does not exist In this study the discharge coefficient CM of triangular labyrinth and sharp crested side weirs are estimated by using artificial neural networks ANN and adaptive neuro fuzzy inference system ANFIS models In this study both the discharge coefficient and the discharge capacity of side weirs are used as the target outputs The results show that the ANN and ANFIS models predict more accurate results than those of other investigators Also the results show that ANN model is more capable for predicting the real discharge coefficient of sharp crested side weirs where as for the triangular labyrinth side weirs the results of discharge coefficient by ANFIS model are more accurate Keywords Sharp Crested Side Weir Labyrinth Side Weir Discharge Coefficient Artificial Neural Network ANN Adaptive Neuro Fuzzy Inference System ANFIS
استاد راهنما :
عبدالرضا كبيري ساماني، رضا حجازي طاقانكي
استاد مشاور :
محمود برقعي
استاد داور :
مريم ذكري، حميدرضا صفوي
