摘要
By applying the aggregation operator γ-operator and introducing a new method for global data contribution, the problems of information loss and the decrease of running efficiency in FuzzyJ Toolkit, an expert system shell, can be effectively solved. The example shows that the approach can overcome imprecision of max-operator and min-operator used during the process of fuzzy reasoning. Therefore, the information accuracy and the system performance can be effectively improved, which promotes the usability of FuzzyJ Toolkit.
运用聚合运算符γ算子和一个全新的方法处理模糊推理中的全局数据贡献 ,可以有效地解决模糊专家系统外壳FuzzyJToolkit在推理过程中出现的信息丢失和运行效率降低问题 .实例分析表明 ,这种方法可以克服系统采用的max ,min操作符所固有的不精确性 ,有效地提高信息的准确性和系统的性能 ,从而增强了系统的可用性 .
基金
theMinisterialLevelFoundation
