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Updated: Sep 13, 2025

Watershed Planning within a Quantitative Scenario Analysis Framework
12:44

Watershed Planning within a Quantitative Scenario Analysis Framework

Published on: July 24, 2016

8.1K

可解释的人工智能驱动的评估水气候相互作用塑造河流排放动态在季风盆地

Prashant Parasar1, Akhouri Pramod Krishna2

  • 1Department of Remote Sensing, Birla Institute of Technology, Mesra, Ranchi, Jharkhand, 835215, India. phdrs10003.20@bitmesra.ac.in.

Scientific reports
|July 27, 2025
PubMed
概括

这项研究引入了一种新的深度学习框架,使用科尔莫戈罗夫·阿诺德网络 (KAN) 和沙普利增量扩展 (SHAP) 来准确地预测季风地区的河流排放情况. 该模型显示了高预测性能,并确定了关键的水气候驱动因素,提供了气候弹性决策支持工具.

关键词:
在CMIP6中,CMIP6是CMIP6.可解释的人工智能科尔摩戈罗夫·阿诺德网络预测河流排放情况SHAP的解释性可以解释.苏巴纳雷卡河流域的河流流域

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