Hybrid Deep Learning Combining Mode Decomposition and Intelligent Optimization for Discharge Forecasting: A Case Study of the Baiquan Karst Spring

Karst springs play a critical strategic role in regional economic and ecological sustainability, yet their spatiotemporal heterogeneity and hydrological complexity pose substantial challenges for flow prediction. This study proposes FMD-mGTO-BiGRU-KAN, a four-stage hybrid deep learning architecture...

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Vydané v:	Sustainability Ročník 17; číslo 18; s. 8101
Hlavní autori:	Li, Yanling, Dong, Tianxing, Shao, Yingying, Mao, Xiaoming
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Basel MDPI AG 01.09.2025
Predmet:	Aquifers Case studies Decomposition method Deep learning Environmental aspects Fault lines Geology Groundwater Hydrology Karst Machine learning Mathematical optimization Natural history Optimization algorithms Prediction theory Springs Stream measurements Stress concentration Technology application Time series China
ISSN:	2071-1050, 2071-1050
On-line prístup:	Získať plný text
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