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使用低成本的传感器网络与人工神经网络/kriging技术来描述PM2.5度的时空分布和微环境来源贡献

Yi-Ming Lee1, Guan-Yu Lin2, Thi-Cuc Le1

  • 1Institute of Environmental Engineering, National Yang Ming Chiao Tung University, Hsinchu, Taiwan.

Environmental research
|December 15, 2023
PubMed
概括

这项研究使用低成本传感器 (LCS) 在城市地区绘制细颗粒物 (PM2.5) 地图,确定交通和工业等特定来源. 这些发现有助于制定有针对性的空气污染控制战略.

关键词:
人工神经网络的人工神经网络低成本的传感器传感器微观环境是一个微观环境.PM(2.5) 的来源贡献.时间空间分布的分布.

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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...