شماره ركورد :
431754
عنوان مقاله :
پيش بيني زمان واقعي سيل با استفاده از شبكه هاي عصبي تركيبي
عنوان به زبان ديگر :
Real-Time Flood Forecasting Using Hybrid Neural Networks
پديد آورندگان :
كوهيان افضل، فرشاد نويسنده Kooyian Afzal, F.
اطلاعات موجودي :
فصلنامه سال 1387
رتبه نشريه :
علمي پژوهشي
تعداد صفحه :
18
از صفحه :
1
تا صفحه :
18
چكيده لاتين :
Hybrid models which are based on methods which divide a complex simulation problem to several simple local models and combine the results, potentially could result in different output. The input space in this method is divided into subspaces, and then some single models are assigned to each specific region of the space. In this research by using some floods generated by a hydrologic model, advantages of hybrid models in real-time flood forecasting compared to global models was investigated. To do this, the results of a global ANN model which simulates whole of the flood processes using a single model, are compared with that of two hybrid models, one consisting of a 4 ANN and the other consisting of 8 ANN. The results shows that hybrid models have significantly better results in flood forecasting specially in forecasting time and amount of peak discharges. This is very important in flood forecasting in flood warning systems because of their important role in flood mitigation activities.
سال انتشار :
1387
عنوان نشريه :
هيدروليك
عنوان نشريه :
هيدروليك
اطلاعات موجودي :
فصلنامه با شماره پیاپی سال 1387
كلمات كليدي :
#تست#آزمون###امتحان
لينک به اين مدرک :
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