一个两阶段的反向智能路径优化模型,用于人类与水之间的关系调节
Qingsong Wu1, Qiting Zuo2, Zhizhuo Zhang3
1School of Water Conservancy and Transportation, Zhengzhou University, Zhengzhou 450001, China; Henan International Joint Laboratory of Water Cycle Simulation and Environmental Protect, Zhengzhou 450001, China.
Water research
|November 21, 2025
概括
这项研究开发了一种两阶段反向智能路径优化模型 (TS_IIPOM) 来调节人与水的关系 (HWR). 该模型通过平衡人类和水系统来优化HWR监管,在河南省显示有效性.
科学领域:
- 环境科学 环境科学
- 水资源管理 水资源管理
- 系统工程 系统工程
背景情况:
- 人与水的关系 (HWR) 是复杂的,需要有效的监管策略.
- 现有的HWR调节方法往往缺乏定量方法和综合优化.
- 了解人类和水系统之间的动态相互作用对于可持续发展至关重要.
研究的目的:
- 开发和应用一种基于和平衡的新型模式来规范人与水之间的关系 (HWR).
- 为了改进管理,将 HWR 监管的定性目标转化为定量表达.
- 为全球HWR研究提供方法论框架和实际见解.
主要方法:
- 使用了"理论-方法-应用"的逻辑框架.
- 开发了一个两阶段的反向智能路径优化模型 (TS_IIPOM),集成了发展趋势,重要性程度,优先级级和更改难度.
- 该模型考虑了行星边界概念中的水资源,经济,社会和生态环境约束,通过智能优化算法解决.
主要成果:
- 该TS_IIPOM有效地合成多源信息,以优化HWR监管路径.
- 在河南省 (2001-2022) 的分析显示,人类和水系统的积极趋势,但相对脱.
- 该研究量化了河南HWR的当前和和平衡度,确定了水系统的歇斯底里和调节路径的空间变化.
结论:
- 该TS_IIPOM是有效的和适用于HWR调节,提供优化的路径.
- 河南的人类水系统呈现脱和水系统歇斯底里,表明需要有针对性的监管.
- 该研究为制定战略提供了坚实的基础,以提高全球和河南省的HWR可持续性.
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