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Improving TIGGE Precipitation Forecasts Using an SVR Ensemble Approach in the Huaihe River Basin
المؤلفون المشاركون
Li, Zhijia
Wang, Jianqun
Cai, Chenkai
المصدر
العدد
المجلد 2018، العدد 2018 (31 ديسمبر/كانون الأول 2018)، ص ص. 1-15، 15ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2018-10-23
دولة النشر
مصر
عدد الصفحات
15
التخصصات الرئيسية
الملخص EN
Recently, the use of the numerical rainfall forecast has become a common approach to improve the lead time of streamflow forecasts for flood control and reservoir regulation.
The control forecasts of five operational global prediction systems from different centers were evaluated against the observed data by a series of area-weighted verification and classification metrics during May to September 2015–2017 in six subcatchments of the Xixian Catchment in the Huaihe River Basin.
According to the demand of flood control safety, four different ensemble methods were adopted to reduce the forecast errors of the datasets, especially the errors of missing alarm (MA), which may be detrimental to reservoir regulation and flood control.
The results indicate that the raw forecast datasets have large missing alarm errors (MEs) and cannot be directly applied to the extension of flood forecasting lead time.
Although the ensemble methods can improve the performance of rainfall forecasts, the missing alarm error is still large, leading to a huge hazard in flood control.
To improve the lead time of the flood forecast, as well as avert the risk from rainfall prediction, a new ensemble method was proposed on the basis of support vector regression (SVR).
Compared to the other methods, the new method has a better ability in reducing the ME of the forecasts.
More specifically, with the use of the new method, the lead time of flood forecasts can be prolonged to at least 3 d without great risk in flood control, which corresponds to the aim of flood prevention and disaster reduction.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Cai, Chenkai& Wang, Jianqun& Li, Zhijia. 2018. Improving TIGGE Precipitation Forecasts Using an SVR Ensemble Approach in the Huaihe River Basin. Advances in Meteorology،Vol. 2018, no. 2018, pp.1-15.
https://search.emarefa.net/detail/BIM-1118881
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Cai, Chenkai…[et al.]. Improving TIGGE Precipitation Forecasts Using an SVR Ensemble Approach in the Huaihe River Basin. Advances in Meteorology No. 2018 (2018), pp.1-15.
https://search.emarefa.net/detail/BIM-1118881
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Cai, Chenkai& Wang, Jianqun& Li, Zhijia. Improving TIGGE Precipitation Forecasts Using an SVR Ensemble Approach in the Huaihe River Basin. Advances in Meteorology. 2018. Vol. 2018, no. 2018, pp.1-15.
https://search.emarefa.net/detail/BIM-1118881
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1118881
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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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
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