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Updated: Jul 6, 2025

Watershed Planning within a Quantitative Scenario Analysis Framework
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Watershed Planning within a Quantitative Scenario Analysis Framework

Published on: July 24, 2016

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一个改进的反向传播神经网络框架及其在城市河流流域雨水管理模型自动校准中的应用

Jiashen Feng1, Tingting Duan1, Junsong Bao1

  • 1State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China.

The Science of the total environment
|January 7, 2024
PubMed
概括

一个改进的框架将主要组件分析 (PCA) 和遗传算法 (GA) 与反向传播神经网络 (BPNN) 结合起来,有效校准了风暴水管理模型 (SWMM). 这种PCA-GA-BPNN方法显著提高了参数预测的准确性,并减少了训练时间.

关键词:
自动参数校准自动参数校准逆向传播神经网络 (BPNN) 是一种神经网络.基因算法 (GA) 处理过程主要组成部分分析 (PCA)风暴水管理模型 (SWMM) 风暴水管理模型城市河流流域的流域

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