Systems Engineering and Electronics

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Optimization algorithm for DS evidence theory based on energy modification and decision set reduction

CHEN Yingchun, LI Ou, SUN Yu   

  1. Information System Engineering College, Information Engineering University, Zhengzhou 450002, China
  • Online:2017-07-25 Published:2010-01-03

Abstract:

In order to improve the anti-noise or anti-jamming performance and to solve the problem of high conflict by using the basic probability assignment and the cardinality of focal elements, the evolution function of prior information ratio for focal elements’ energy is introduced to modify the evidence source and the combination rule of Dempster-Shafer(DS) evidence theory. For reducing the computation complexity, the trust value assignment of the multiple focal elements to single focal elements and the reduction of the decision set are presented to optimize the adaptability of the modification algorithm for big data. The experiment results prove that the optimization algorithm is accurate and effective.

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