Tao Liu1, Kejia Zhang1,*, Jingsong Yin1, Yan Zhang1, Zihao Mu1, Chunsheng Li1, Yanan Hu2
Computer Systems Science and Engineering, Vol.47, No.2, pp. 2563-2582, 2023, DOI:10.32604/csse.2023.041228
Abstract Spatio-temporal heterogeneous data is the database for decision-making in many fields, and checking its accuracy can provide data support for making decisions. Due to the randomness, complexity, global and local correlation of spatiotemporal heterogeneous data in the temporal and spatial dimensions, traditional detection methods can not guarantee both detection speed and accuracy. Therefore, this article proposes a method for detecting the accuracy of spatiotemporal heterogeneous data by fusing graph convolution and temporal convolution networks. Firstly, the geographic weighting function is introduced and improved to quantify the degree of association between nodes and calculate the weighted adjacency value to simplify the… More >
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