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PCA嵌入通过其统计和数据驱动性质有效缓解了三个关键挑战,同时保持捕捉基本时空关系的能力。 形式上,由于交通数据的固有周期性,我们首先将每一天划分为相等的时间槽以获得(Z\in R^{D\times N\times T}),其中(D)是天数,(N)表示节点数量,(T)是一天中的时间槽数量(例如,以5分钟采样间隔,(T = 288))。然后我...
It can facilitate the public diplomacy of EU in Indonesia. For Indonesia, the direct interaction through PCA provides an opportunity to gain a bigger support from the EU, which is significant to back up the current achievement of Indonesia and the effort to raise its international posture. ...
然后我们应用PCA以获得每天的嵌入矩阵:(E_{d_{pca}} = Z_d\cdot P\in R^{N\times C}),(d\in{1,…,D}),其中(P)是由PCA生成的投影矩阵,(C)是PCA嵌入的维度。随后,我们对所有训练日的PCA嵌入进行平均以获得最终的节点表示: # 计算PCA嵌入矩阵的代码示例(可修改变量名等)...
然后我们应用PCA以获得每天的嵌入矩阵:(E_{d_{pca}} = Z_d\cdot P\in R^{N\times C}),(d\in{1,…,D}),其中(P)是由PCA生成的投影矩阵,(C)是PCA嵌入的维度。随后,我们对所有训练日的PCA嵌入进行平均以获得最终的节点表示: # 计算PCA嵌入矩阵的代码示例(可修改变量名等)...
形式上,由于交通数据的固有周期性,我们首先将每一天划分为相等的时间槽以获得(Z\in R^{D\times N\times T}),其中(D)是天数,(N)表示节点数量,(T)是一天中的时间槽数量(例如,以5分钟采样间隔,(T = 288))。然后我们应用PCA以获得每天的嵌入矩阵:(E_{d_{pca}} = Z_d\cdot P\in R^{N\times C}...
[11]Fon, A.N., Che, V.B. and Suh, C.E. (2012) Application of Electrical Resistivity and Chargeability Data on a GIS Platform in Delineating Auriferous Structures in a Deeply Weathered Lateritic Terrain, Eastern Cameroon. International Journal of Geosciences, 3, 960-971. ...
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[60] BlumenthalJ, Megherbi D B, Lussier R. Unsupervised machine learning via Hidden MarkovModels for accurate clustering of plant stress levels based on imagedchlorophyll fluorescence profiles & their rate of change in time[C]//2014IEEE International Conference on Computational Intelligence and Virtual...