Keywords: risk analysis, morphogenetic systems, tensor calculus, prototype fields, fuzzy rules, risk assessment, fuzzy sets, uncertainty
The morphogenetic system in risk analysis
Modern uncertainty theories (fuzzy logic, information diffusion) provide a calculus to obtain a relationship through an observation pattern. With the relationship obtained, we can estimate the risk in different situations. We know that the information structure is essential to forecast the future risk in different situations. The main difficulty in forecasting the risk is in extracting the rules from a noncoherent set of data. Fuzzy sets and fuzzy rules are essential to detect the uncertainty, but are not sufficient to define in an optimal way the rules that describe the relationship among fuzzy variables. This paper presents the morphogenetic system, which projects the output samples of fuzzy sets to the input samples of the fuzzy sets. In the projection operator, we compute the best rules for the inferential or reasoning process.