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المؤلفShaofu, Ma
المؤلفAl-Juboori, Anas Mahmood
المؤلفAlwan, Asmaa Hussein
المؤلفAbdel-Salam, Abdel-Salam G.
تاريخ الإتاحة2023-11-29T10:06:02Z
تاريخ النشر2021
اسم المنشورComplexity
المصدرScopus
الرقم المعياري الدولي للكتاب10762787
معرّف المصادر الموحدhttp://dx.doi.org/10.1155/2021/3721661
معرّف المصادر الموحدhttp://hdl.handle.net/10576/49814
الملخصStreamflow is associated with several sources on nonstationaries and hence developing machine learning (ML) models is always the motive to provide a reliable methodology to understand the actual mechanism of streamflow. The current research was devoted to generating monthly streamflows from annual streamflow. In this study, three different ML models were applied for this purpose, including Multiple Additive Regression Trees (MART), Group Methods of Data Handling (GMDH), and Gene Expression Programming (GEP). The models were developed based on annual streamflow and monthly time index of three rivers (i.e., Upper Zab, Lower Zab, and Diyala) located in the north region of Iraq. The modeling results indicated an optimistic simulation for generating the monthly streamflow time series from annual streamflow time series. The potential of the MART model was superior to the GMDH and GEP models for Upper Zab River (R2 0.84, 0.64, and 0.47), Lower Zab River (R2 0.75, 0.46, and 0.40), and Diyala River (R2 0.78, 0.42, and 0.5). The results of RMSE were 113, 169, and 208 for Upper Zab River, 95, 149, and 0.5 for Lower Zab River, and 73, 118, and 109 for Diyala River. The results have proved the possibility of changing the timescale in generating streamflow data.
اللغةen
الناشرHindawi Limited
الموضوعData handling
Gene expression
Machine learning
Rivers
Time series
Trees (mathematics)
Additive regression
Gene expression programming
Machine learning models
Model results
Optimistic simulation
River flow
Time index
Time-scales
Stream flow
العنوانOn the Investigation of Monthly River Flow Generation Complexity Using the Applicability of Machine Learning Models
النوعArticle
رقم المجلد2021
dc.accessType Abstract Only


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