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WSN clustering data fusion algorithm based on evidence theory

2013-09-18
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In a sensor network, there is a great deal of uncertainty in the recognition results of multiple sensors for the same target. As an imprecise reasoning method in the field of target recognition, evidence theory can effectively fuse the uncertain data of multiple sensors to obtain reasonable judgments. The algorithm in this paper uses evidence entropy and evidence distance function to screen cluster heads, determine cluster member nodes and candidate evidence information, effectively reducing the redundant information within the cluster and the amount of cluster head calculation, improving the accuracy of data fusion, and providing users with more reliable information to determine the target type and its location.

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