Study on Evaluation Method for Intelligence Processing System with Incomplete Information

Qing-e Guo, Bing Su


The evaluation and optimization of intelligence processing system is very important for any decision maker, because the information who gives is the basis of next action. Using the idea of DEA cross-evaluation for reference, the evaluation model for intelligence processing system under partial weight information is established. Assumed each of the system is self-serving to maximize its evaluation value and cross-evaluated others adopting weights which could compete for its goal; Integrated values of cross-evaluation results are used as decision criteria.


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