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使用深度学习的有毒城市羽毛的时空空间预测

Yinan Wang1, M Giselle Fernández-Godino2, Nipun Gunawardena2

  • 1Department of Industrial and Systems Engineering, Rensselaer Polytechnic Institute, Troy, NY 12180, USA.

PNAS nexus
|June 30, 2025
PubMed
概括

一个新的深度学习模型,ST-GasNet,准确地预测了城市地区的有毒烟雾分散. 这种人工智能方法为应急响应提供了快速可靠的预测,优于传统的计算流体动力学模型.

关键词:
复杂的地形,复杂的地形.气体分散气体的分散气体时间空间预测预测.有毒的羽毛有毒的羽毛城市环境城市环境

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Linear Approximations01:23

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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...