Abstract
In temporal information fusion, the information collected by sensors is obtained dynamically with the passage of time. Unlike the spatial information fusion, temporal fusion should be dynamic. Evidence theory has been applied to fuse temporal and spatial information; however, existing temporal fusion methods do not treat conflicting and non-conflicting evidence sources distinctively. Moreover, unlike spatial evidence sources, which are obtained simultaneously, temporal evidence sources cannot be evaluated simultaneously to obtain their degree of reliability. Thus, it is necessary to develop a method for temporal evidence combination. In this paper, a self-adaptive combination method for temporal evidence is proposed based on the negotiation strategy. In the proposed method, a set called an evidence set is constructed by the cumulative temporal fusion results of the previous moment, current moment, and future moment. The evidence set is evaluated as conflicting or non-conflicting according to the maximum power pignistic probability distance between each pair of evidence sources in the set. Then, temporal evidence sources are self-adaptively combined by different methods according to the degree of conflict. Numerical experiments were conducted to evaluate the performance of the proposed method. The results indicated that the proposed method is sufficiently effective and robust to support decision making.
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Acknowledgements
This work was supported by National Natural Science Foundation of China (Grant Nos. 61703426, 61876189, 61806219), China Post-Doctoral Science Foundation (Grant No. 2018M633680), Young Talent Fund of University Association for Science and Technology in Shaanxi, China (Grant No. 20190108), and Innovation Talent Supporting Project of Shaanxi, China (Grant No. 2020KJXX-065).
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Song, Y., Zhu, J., Lei, L. et al. Self-adaptive combination method for temporal evidence based on negotiation strategy. Sci. China Inf. Sci. 63, 210204 (2020). https://doi.org/10.1007/s11432-020-3045-5
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DOI: https://doi.org/10.1007/s11432-020-3045-5