Open AccessNeural Network System Design for Predicting MIN Reliability
Author(s) -
Shilpa Gupta,
Bindu Thakral
Publication year - 2020
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.g5732.059720
Subject(s) - reliability (semiconductor) , computer science , artificial neural network , path (computing) , fault tolerance , multistage interconnection networks , interconnection , reliability engineering , artificial intelligence , topology (electrical circuits) , distributed computing , engineering , computer network , power (physics) , physics , electrical engineering , quantum mechanics
Efforts have been made to examine and study different path and multi-path Multistage Interconnection Networks (MIN) possessing regular or irregular topology. Numerous strategies for establishing fault-tolerance in MINs have also been studied. These studies have provided us help to understand the strength and weakness of the existing static and dynamic and regular and irregular MINs. Application of Neural Networks leads to the development of MINs with improved performance and study of its Reliability In this paper ANN based system has been developed which will help in the study of metrics required for enhancing and predicting the reliability of MINs. In this paper Number of iterations are conducted to improve the ANN based system to predict the reliability of MINs by changing the number of neurons and the number of layers.