针对体系效能评估中仿真结果数据的转化和聚合问题，提出采用效用函数方法加以解决。
To solve the problem of transforming and aggregating of simulation result data in effectiveness evaluation of armor weapon system-of-systems, the utility functions method is put forward.
该方法既克服了期望值-差法和夏普指数法的不足，又在一定程度上避免了效用函数构造的困难。
The new method has overcomed the shortcomings of the Expectation-Variance method and Sharpe's Index method, and avoids the inconvenience of constructing utility function to a certain extent as well.
其次，提出了基于属性效用函数估计的学习样本构造方法，从决策问题本身抽取学习样本。
Secondly, to extract learning samples from the MADM problem, an approach to estimate the utility functions for attributes is presented.
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