基于证据理论的迭代多步预测方法研究

Iterative multi-step prediction model based on theory of evidence

中文关键词  证据理论  迭代多步预测  滑动窗口

英文关键词  theory of evidence  iterative multi-step predicting  sliding widow

中文摘要

      为了有效利用复杂非线性工程系统中各种不确定信息和主观知识, 本文结合相空间重构理论和证据推理理论, 建立时序证据的多步预测模型. 本文先对时序证据进行相空间重构; 针对时序证据预测中信息量大且存在误差累积的不足, 采用时序证据滑动窗口处理方法, 以降低累积误差; 窗口内运用迭代融合规则, 以降低信息量的存储. 将该模型应用于某型陀螺仪漂移预测, 试验结果证明, 本文方法能够有效降低迭代时产生的累积误差和信息量, 结论更接近实际情况.

英文摘要

      To make use of the uncertain information and subjective knowledge in complex nonlinear systems, we propose a multi-step prediction method for time series of evidence based on the phase space reconstruction theory and evidence inference theory. In the reconstruction of phase space for time series of evidence, we use the sliding window for time series of evidence to deal with the great amount of information and the shortage of accumulation errors to reduce the accumulated errors. The information storage is reduced by applying the iterative rules to the windows. The proposed methods have been applied to the simulation tests of a missile inertia device for fault prediction. The results show the effectiveness of these methods.