Affiliations:
JiangXi University of Finance and Economics, School of Information Management, Nanchang, China
Correspondence:
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Corresponding author. Bo Yang, JiangXi University of Finance and Economics, School of Information Management, Nanchang, China. E-mail: [email protected].
Abstract: Taking the dynamic risk identification as the research object, propose a risk identification model of dynamic memory and variable fuzzy identify based on the immune mechanism extension, DRIBIEM. According to the dynamic risk characteristics which is complex and uncertain, DRIBIEM dynamically maps the intensity and frequency of risk to the concentration of antigen, based on the cell death pattern, stimulates immune memory, guides the evolution of antibodies and controls life cycle of identifier by antigen concentration which solves the problem that the traditional immune identification algorithm takes too long time, realizes the distributed automatic updating of identifiers and improves the dynamic risk identification ability. Simulation results show that DRIBIEM fully reflects the dynamic characteristics of immune memory and can effectively identify the complex dynamic risks. Its feasibility can be verified in the practical application of dynamic risk identification.
