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Updated: Jun 10, 2026

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基于3D-EEM和卷积神经网络的平原河流网络地区农业表面污染源的识别

Juan Huan1, Jialong Yuan2, Hao Zhang2

  • 1School of Computer and Artificial Intelligence, School of Alibaba Cloud Big Data, School of Software, Changzhou University, Changzhou 213100, China

Water science and technology : a journal of the International Association on Water Pollution Research
|April 28, 2024
PubMed
概括

一个新的RA-GoogLeNet模型使用光光谱数据准确识别农业有机污染. 这种方法提高了河流网络中的水质监测和可追溯性,保护生态系统和健康.

关键词:
农业非点源污染源的污染.注意力机制注意力机制卷积神经网络是一种卷积神经网络.深度学习是一种深度学习.平原河流网络区域 平原河流网络区域这是一个三维光灯.

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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...