Improvement of Time Series Data Fusion Based on Evidence Theory and DEMATEL

Abstract

Time series data fusion has been widely used in practice and has received great attention in recent years. From the perspective of analyzing the correlation between data, this paper proposed a new accurate time series data fusion algorithm based on the decision making trial and evaluation laboratory (DEMATEL) model. With the analysis of various factors in DEMATEL and the combination of ordered weight aggregation operator (OWA) algorithms, the impact of time interval on the results of the fusion is reduced. The example given in this paper is a good illustration of the efficiency and feasibility of the new algorithm. We believe that the improvement work in this paper not only promotes the theoretical prediction of data fusion but also plays an important role in various fields.

Keywords

• Credibility decay model
• time series
• data fusion
• ordered weight aggregation operator (OWA)
• decision making trial and evaluation laboratory (DEMATEL)
• target recognition