PREDICTION OF FLOOD IN KARKHEH BASIN USING DATA-DRIVEN METHODS
Abstract. 2 and RMSE of 85.89% and 30.02 m3/s during testing periods, respectively. Similarly, LSSVM model performed better in predicting annual maximum streamflow in comparison with other machine learning models.
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
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Online-Ressource
- Language
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Englisch
- Bibliographic citation
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PREDICTION OF FLOOD IN KARKHEH BASIN USING DATA-DRIVEN METHODS ; volume:X-4/W1-2022 ; year:2023 ; pages:349-354 ; extent:6
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences ; X-4/W1-2022 (2023), 349-354 (gesamt 6)
- Creator
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Kamali, S.
Saedi, F.
Asghari, K.
- DOI
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10.5194/isprs-annals-X-4-W1-2022-349-2023
- URN
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urn:nbn:de:101:1-2023011904463577273953
- Rights
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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15.08.2025, 7:29 AM CEST
Data provider
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Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Kamali, S.
- Saedi, F.
- Asghari, K.
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