Massive Information Fusion Algorithm and Its Application in Status Evaluation
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    Abstract:

    To solve the problem that the evidence theory can’t efficiently deal with the fusion of massive information, a new method combining clustering and the convex evidence theory is put forward. The method aims to solve the common and important application problems of the status evaluation. First, the famous clustering algorithm BIRCH is performed to pre-process the data, generating multiple clusters. Second, the centroid of each cluster is calculated as the representation of the cluster pertaining to the fact that most data used for status evaluation have numeric attribute or ordinal attribute. Then, to form the evidence provided by the information in each cluster, the centroid information is given a basic probability assignment value based on the generalized triangular fuzzy membership function. Finally, evidences are combined according to the combination rule of the convex evidence theory. As a result, the massive information fusion is achieved. The results of simulation experiment show that the presented method can efficiently and reasonably perform the massive information fusion, providing a new way to improve the massive information fusion techniques.

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李嘉菲,周斌,刘大有,胡亮,王峰.海量信息融合方法及其在状态评价中的应用.软件学报,2014,25(9):2026-2036

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History
  • Received:January 20,2014
  • Revised:April 09,2014
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  • Online: September 09,2014
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