开放系统中的信任关系本质上是最复杂的社会关系之一，涉及假设、期望、行为和环境多种因子，很难准确地定量表示和预测。本文在现有的基于行为监控的动态信任模型的基础上，把粗糙集理论和信息熵理论结合起来应用于信任度量与预测模块。通过实验证明，新的条件信息熵权重确定方法可以解决原有权重确定方法自适应性差和行为数据规模的扩展能力差的问题。

In an open system,trust is one of the most complex concepts in social relationships,involving many decision factors,such as assumptions,expectations and behaviors,etc. So,it is very difficult to quantify and forecast accurately. Combined with rough set and information entropy,a new dynamic trust forecasting model is proposed.Experiments show  that the new method of weight determined by conditional information entrophy can solve the problems of the bad selfadaptation and the poor data scale expansion ability  brought by the original weight determination.