Generic reconstruction technology based on RST for multivariate time series of complex process industries

来源期刊:中南大学学报(英文版)2012年第5期

论文作者:孔玲爽 阳春华 李建奇 朱红求 王雅琳

文章页码:1311 - 1316

Key words:complex process industry; prediction model; multivariate time series; rough sets

Abstract:

In order to effectively analyse the multivariate time series data of complex process, a generic reconstruction technology based on reduction theory of rough sets was proposed. Firstly, the phase space of multivariate time series was originally reconstructed by a classical reconstruction technology. Then, the original decision-table of rough set theory was set up according to the embedding dimensions and time-delays of the original reconstruction phase space, and the rough set reduction was used to delete the redundant dimensions and irrelevant variables and to reconstruct the generic phase space. Finally, the input vectors for the prediction of multivariate time series were extracted according to generic reconstruction results to identify the parameters of prediction model. Verification results show that the developed reconstruction method leads to better generalization ability for the prediction model and it is feasible and worthwhile for application.

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