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Updated: Jun 28, 2026

Continuous Instream Monitoring of Nutrients and Sediment in Agricultural Watersheds
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Continuous Instream Monitoring of Nutrients and Sediment in Agricultural Watersheds

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一种混合深度学习方法,使用常规监控数据预测每小时的河流酸盐度

Yue Hu1, Chuankun Liu2, Wilfred M Wollheim3

  • 1State Key Laboratory of Geohazard Prevention and Geoenvironment Protection (Chengdu University of Technology), Chengdu, 610059, China.

Journal of environmental management
|May 11, 2024
PubMed
概括

这项研究开发了一种深度学习模型,使用常规水质数据预测每小时河流酸盐 (NO3-N) 度. 混合CNN-LSTM模型准确预测酸盐水平,更短的输入数据长度显示出卓越的性能.

关键词:
在美国,CNN是CNN.数据预处理数据的预处理.这是LSTM的LSTM.酸盐出口模式的发展趋势预测酸盐的情况

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相关概念视频

Linear Approximations01:23

Linear Approximations

For a differentiable function of two variables, linear approximation estimates values near a known point by replacing the curved surface with its tangent plane. Consider the function\begin{equation*}f(x,y)=x^2+3y^2\end{equation*}near the point (2, 1). The exact value at this point is f(2, 1) = 22 + 3(1)2 = 4 + 3 = 7.The linear approximation of f(x, y)) near (a, b) is\begin{equation*}L(x,y)=f(a,b)+f_x(a,b)(x-a)+f_y(a,b)(y-b)\end{equation*}First, compute the partial derivatives: fx(x, y) = 2x and...