Reliability and profit function improvement of acyclic transmission network using artificial neural network

Abstract

In this paper, we have examined the reliability and profit function of the acyclic transmission network with the application of the Markov process and artificial neural network. To examine the reliability of the acyclic transmission network, first of all, we have combined the concepts of the Markov process and minimal cuts incorporating copula in repair. The complete failed state of the acyclic transmission network is repaired with the help of two different repair rates, namely, general and exponential which has been incorporated by the application of the Gumbel-Hougaard family of the copula. Once reliability is obtained by the proposed method, then it has been improved with the help of the artificial neural network. A numerical example has been taken to compare the results obtained in this paper.