Modeling of identification for fuzzy system symptoms: an aggregated statistics based approach

Most previous studies concerning "yes or no" binary logic can not provide methods for identifying symptoms of fuzzy systems in the real world. On the basis of aggregated statistics, this paper presents a new approach, called the fuzzy causality network analyzing (FCNA) model, which will help to diagnose the complex world through decomposition and synthesis technologies. A case study is conducted using an example of the light industry development in Jilin Province of China. Results show that this FCNA model can not only integrate more than one person\´s opinions but also quickly locate the life-and-death factors constraining system\´s further development