Evaluation for Result-Chain Models based on Fuzzy Evaluation Matrix

Abstract

Result-Chain based Modeling is a new system analysis and process modeling method. This paper defines Node Influence Degree (NID) to evaluate importance of nodes in a system (RCM model), so to help people to understand the system better. Both qualitative and quantitative evaluation method are described. In the qualitative evaluation method, out-degree and in-degree of a node in system model (and/or digraph) are criterions of NID and system model. Further more, the quantitative evaluation method is proposed on the basis of fuzzy evaluation matrix and sets of adjacent nodes L(i). Quantitative method takes potential influence of nodes into account and gives more precise NID values. As a result, more accurate evaluation gives more support to system analyses and decision making. The model evaluation method makes RCM modeling more perfect technically.