This paper presents a novel approach of radar station intelligence quality evaluation which based on fuzzy Backpropagation neural network (BPNN). Firstly, the index system of the radar station intelligence quality evaluation is established according to the analysis of the process, the characteristics, and the main influencing factors of the radar station intelligence production. And then the factor set, comment set and the membership matrix are structured, the fuzzy BPNN for evaluating the quality of the radar station intelligence is designed referring to the index system. Finally, the experiment shows that the accuracy and stability can be improved effectively by using fuzzy BPNN to evaluate the radar station intelligence quality
The Proportional Conflict Redistribution (PCR) rules based on Dezert-Smarandache theory (DSmT) is a useful method for dealing with uncertainty problems. It is more efficient in combining conflicting evidence. Therefore, it has been successfully applied in identity identification. However, there exist shortcomings in PCR rule. So in this paper we propose a new improved rule which is based on new Proportional Conflict Redistribution. The six PCR rules (PCR1-PCR6) and improved PCR rule are analyzed and compared through numerical examples, and the results show that the improved rule is effective.
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