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Asynchronous parallel surrogate optimization aided neural network design with variable evaluation runtime for streamflow and pollutant forecast

delete2025-10-08
delete0
PRE
AI
夏尉 封面图
夏尉 (Wei Xia) *
W
Wei Lü
C
Chi Zhang
C
Christine A. Shoemaker
DOI：10.1016/j.jhydrol.2025.134378delete
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摘要

摘要

En 中文
• 水文预报中的超参数优化（HPO）具有高度多模态性和评估运行时间可变性。 • 提出一种用于神经网络模型HPO的新型异步并行代理全局优化方法，即ASONN。 • ASONN相比异步并行全局优化方法，可加速HPO达60%。

期刊

Journal of Hydrology 封面图
Journal of Hydrology
IF:
6.3
论文数:
2.4W
被引数:
9.8W

机构

D
Dalian University of Technology
学者数:
6.0W
论文数: 4.4W
被引数: 5.5W
A
ant group
学者数:
237
论文数: 119
被引数: 0
N
National University of Singapore
学者数:
7.6W
论文数: 6.5W
被引数: 11.4W
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