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Jian Zhang, Zhaoguang Hu, Yanan Zheng, Yuhui Zhou and Ziwei Wan
Unlike existing studies focused on the causal relationship between electricity consumption and economic growth at the macro level, this paper uses monthly data from January 2006 to December 2015 and applies the correlation coefficient, as well as Kullbac...
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Yuefeng Cen, Mingxing Luo, Gang Cen, Cheng Zhao and Zhigang Cheng
It is meaningful to analyze the market correlations for stock selection in the field of financial investment. Since it is difficult for existing deep clustering methods to mine the complex and nonlinear features contained in financial time series, in ord...
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Marco Scutari
Bayesian networks (BNs) are a foundational model in machine learning and causal inference. Their graphical structure can handle high-dimensional problems, divide them into a sparse collection of smaller ones, underlies Judea Pearl?s causality, and determ...
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Yi Zhang, Lanxin Qiu, Yangzhou Xu, Xinjia Wang, Shengjie Wang, Agyemang Paul and Zhefu Wu
Software-Defined Networking (SDN) enhances network control but faces Distributed Denial of Service (DDoS) attacks due to centralized control and flow-table constraints in network devices. To overcome this limitation, we introduce a multi-path routing alg...
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Han Zheng, Zanyang Cui and Xingchen Zhang
Driving modes play vital roles in understanding the stochastic nature of a railway system and can support studies of automatic driving and capacity utilization optimization. Integrated trajectory data containing information such as GPS trajectories and g...
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