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Data fusion using fuzzy measures and genetic algorithms

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3 Author(s)
Shuong Tong ; Dept. of Control Eng., Harbin Inst. of Technol., China ; Yi Shen ; Zhiyan Liu

This paper proposes an improvement on the fusion method presented previously (1994, 1998). In those methods not only the reliabilities of the sensors are not considered but also the choice of parameter k is relevant to the number of sensors and whether there is opinion close to 0.5. In our method Genetic Algorithms (GA) is used to find the optimal values for the reliabilities of sensors and fuzzy inference rules for determining the parameter k in multi-sensor fusion. Multi-step fusion and one-step fusion methods are formed based on the fusion functions. Simulation results show the effectiveness of the proposed methods

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Instrumentation and Measurement Technology Conference, 2000. IMTC 2000. Proceedings of the 17th IEEE  (Volume:2 )

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