The data clustering based dynamic risk identification of biological immune system: mechanism, method and simulation

Abstract

Under the new form of economic development in our country, with the growth of dynamic and the complexity of internal and external environment of enterprise, various kinds of uncertain events have emerged in an endless so that the risks faced by enterprises are increasing, how to effectively identify and control dynamic risks for managers are key elements for the sustainable development of enterprises. Biological immune system is a complex adaptive system, can quickly identify and resist the risk, draw lessons from this principle, the biological immune provides a new idea and method to identify dynamic risk effectively for the enterprise. Combing with the literatures, we found that there is a certain progress about the current research of enterprise dynamic risk identification under biological immune perspective, but there is not a set of relatively mature method system. Therefore, this article makes reference to the ideas of the biological immune, on the basis of immune identification mechanism, from two aspects of dynamic risk definition and ascension of identification accuracy to implement extensions of dynamic risk identification of biological immune mechanism, build a set of DRI biological immune system extension method contains dynamic memory automatic identification and variable fuzzy automatic identification system, and carry out the simulation experiment of multi-agent on Netlogo simulation platform to verify the effectiveness of this method. This study extend and expand the enterprise dynamic risk identification theory, enrich the literature of biological immune mechanism of enterprise dynamic risk identification, provide application guide on the problem of dynamic risk identification in other areas.