A novel visibility graph transformation of time series into weighted networks

Abstract Analyzing time series from the perspective of complex network has interested many scientists. In this paper, based on visibility graph theory a novel method of constructing weighted complex network from time series is proposed. The first step is to determine the weights of vertices in time series, which linearly combines the weights generated by induced ordered averaging aggregation operator (IOWA) and visibility graph aggregation operator (VGA). Then, two strategies, averaging strategy and gravity strategy, are proposed to construct weighted network. To testify the validity of proposed method, an artificial case is adopted, in which link prediction is used to evaluate the performance of the weighted network. It is shown that the weighted network constructed by proposed method greatly outperforms the unweighted network obtained by traditional visibility graph theory.

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