Reservoir operation by artificial neural network model : Mosul Dam-Iraq, as a case study
العناوين الأخرى
تشغيل الخزان باستخدام الشبكة العصبية الصناعية : سد الموصل كحالة دراسية
المؤلفون المشاركون
Mustafa, Iyad Salibi
al-Arid, Hasan Hadi Mahdi
Khayyun, Thair Sharif
المصدر
Engineering and Technology Journal
العدد
المجلد 33، العدد 7A (31 يوليو/تموز 2015)، ص ص. 1697-1714، 18ص.
الناشر
تاريخ النشر
2015-07-31
دولة النشر
العراق
عدد الصفحات
18
التخصصات الرئيسية
الموضوعات
الملخص EN
Reservoir operation forecasting plays an important role in managing water resources systems.
Artificial Neural Network (ANN) model was applied for Mosul-Dam reservoir which is located on Tigris River, which the objectives of water resources development and flood control.
Feed-forward multi-layer perceptions (MLPs) are used and trained with the back-propagation algorithm, as they have a high capability of data mapping.
The data set has a period of 23 years from 1990 to 2012..The Input data were inflow (It), evaporation (Et), rainfall (Rt), reservoir storage (St) and outflow (Ot).
The best convergence after more than 1000 trials was achieved for the combination of inflow (It), inflow (It-1), inflow (It-2), evaporation (Et), reservoir storage (St), rainfall (Rt), outflow (Ot-1) and outflow (Ot-2) with error tolerance, learning rate, momentum rate, number of cycles and number of hidden layers as 0.001, 1, 0.9,50000 and 9 respectively.
The coefficient of determination (R2) and MAPE were (0.972) and (17.15) respectively.
The results of ANN models for the training, testing and validation were compared with the observed data.
The predicted values from the neural networks matched the measured values very well.
The application of ANN technique and the predicted equation by using the connection weights and the threshold levels, assist the reservoir operation decision and future updating, also it is an important Model for finding the missing data.
The ANN technique can accurately predict the monthly Outflow.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Khayyun, Thair Sharif& Mustafa, Iyad Salibi& al-Arid, Hasan Hadi Mahdi. 2015. Reservoir operation by artificial neural network model : Mosul Dam-Iraq, as a case study. Engineering and Technology Journal،Vol. 33, no. 7A, pp.1697-1714.
https://search.emarefa.net/detail/BIM-629889
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Khayyun, Thair Sharif…[et al.]. Reservoir operation by artificial neural network model : Mosul Dam-Iraq, as a case study. Engineering and Technology Journal Vol. 33, no. 7A (2015), pp.1697-1714.
https://search.emarefa.net/detail/BIM-629889
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Khayyun, Thair Sharif& Mustafa, Iyad Salibi& al-Arid, Hasan Hadi Mahdi. Reservoir operation by artificial neural network model : Mosul Dam-Iraq, as a case study. Engineering and Technology Journal. 2015. Vol. 33, no. 7A, pp.1697-1714.
https://search.emarefa.net/detail/BIM-629889
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references : p. 1713-1714
رقم السجل
BIM-629889
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر