Improved monthly runoff time series prediction using the SOA–SVM model based on ICEEMDAN–WD decomposition

التفاصيل البيبلوغرافية
العنوان:	Improved monthly runoff time series prediction using the SOA–SVM model based on ICEEMDAN–WD decomposition
المؤلفون:	Xu, DM, Wang, X, Wang, WC, Chau, KW, Zang, HF
المساهمون:	Department of Civil and Environmental Engineering
بيانات النشر:	International Water Association Publishing
سنة النشر:	2023
المجموعة:	Hong Kong Polytechnic University: PolyU Institutional Repository (PolyU IR)
مصطلحات موضوعية:	Improved complete ensemble EMD (ICEEMDAN), Monthly runoff prediction, Quadratic decomposition, Seagull optimization algorithm (SOA), Support vector machine (SVM), Wavelet decomposition (WD)
الوصف:	202307 bckw ; Version of Record ; Others ; Special project for collaborative innovation of science and technology in 2021; Henan Province University Scientific and Technological Innovation Team ; Published ; IWAP (2023) -“Subscribe to Open” since 2021 ; TA
نوع الوثيقة:	article in journal/newspaper
اللغة:	English
تدمد:	1464-7141
Relation:	http://hdl.handle.net/10397/99565; 943; 970; 25; OA_Others
DOI:	10.2166/hydro.2023.172
الاتاحة:	http://hdl.handle.net/10397/99565 https://doi.org/10.2166/hydro.2023.172
Rights:	© 2023 The Authors ; This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (CC BY 4.0), which permits copying, adaptation and redistribution, provided the original work is properly cited (http://creativecommons.org/licenses/by/4.0/). ; The following publication Xu, D. M., Wang, X., Wang, W. C., Chau, K. W., & Zang, H. F. (2023). Improved monthly runoff time series prediction using the SOA–SVM model based on ICEEMDAN–WD decomposition. Journal of Hydroinformatics, 25(3), 943-970 is available at https://doi.org/10.2166/hydro.2023.172.
رقم الانضمام:	edsbas.29BBB643
قاعدة البيانات:	BASE

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الوصف
تدمد:	14647141
DOI:	10.2166/hydro.2023.172