Gene Regulatory Network Approach for Failure Rate Prediction in Distributed Systems

This paper proposes a new paradigm for distributed biologically inspired computing that is derived from gene regulatory networks, for classification problems. Gene regulatory networks are models of genes and dynamic interactions that take place between them. The differential equation representations of such networks resemble both recurrent neural networks as well as idiotypic networks in immune systems, although more complex than either. The proposed method of classification is then applied to predict the failure rate power distribution systems. Results of this study provide further insights into the new scheme.