Bi-level Multi-objective Complex Regional Water Resources Optimal Allocation Model Under Hybrid Uncertainty

To address the coordinated balance between ecological protection and economic benefits in water resources allocation under complex uncertain environments, this paper employs fuzzy random theory to quantify the uncertainty characteristics of the water resources system. Radial Basis Function Neural Ne...

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Vydáno v:	Water resources management Ročník 39; číslo 13; s. 7023 - 7058
Hlavní autoři:	Wang, Tao, Duan, Jingjing, Jiang, Chenhui, Zhang, Zhaohan, Wang, Dangxian, Li, Xing, Guan, Ziyu, Zhao, Jing, Zhai, Jiaqi, Liu, Jingzhe, Gao, Yulong, Wang, Peiling
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Dordrecht Springer Netherlands 01.10.2025 Springer Nature B.V
Témata:	Atmospheric Sciences Civil Engineering Conflict management Data analysis Decision making Earth and Environmental Science Earth Sciences Economic benefits Economics Environment Fuzzy sets Geotechnical Engineering & Applied Earth Sciences Hydrogeology Hydrology/Water Resources Inflow Integer programming Linear programming Machine learning Managers Mathematics Mixed integer Multiple objective analysis Neural networks Nonlinear response Normal distribution Optimization Population growth Probability distribution Radial basis function Random variables Rationality Resource allocation River basins Rivers Set theory Socioeconomic factors Stochastic programming Supply & demand Sustainable development Sustainable Development Goals Uncertainty Water diversion Water levels Water resources Water resources management Water shortages Water supply Water use Watershed management Watersheds Hybrid uncertainty Water resources allocation Bi-level optimization KKT Machine learning
ISSN:	0920-4741, 1573-1650
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