A fuzzy causality network analyzing approach to identifying systematic symptoms

摘要

The conventional "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 fuzzy causality network analyzing [FCNA) model, which will help to diagnose the complex world through decomposition and synthesis technologies. A case study concerning the development of light industry in Jilin Province of P.R. China is conducted in detail. 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.