Combining time series and neural network approaches for modeling reliability growth

Chao Ton Su*, Lee-Ing Tong, Chee Ming Leou

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

34 Scopus citations

Abstract

Reliability forecasting assists the manager to efficiently track the operational performance and the system's reliability for follow-up actions. This study combines time series and neural network approaches to predict the system's reliability. Prediction of the time series based on the previous parameter value is used as the neural network's input. The proposed method can enhance the reliability forecasting ability and accelerate the convergence of network training. Moreover, two case studies are presented to demonstrate the effectiveness of the proposed procedure.

Original languageEnglish
Pages (from-to)419-430
Number of pages12
JournalKung Yeh Kung Chieng Hsueh K'an/Journal of the Chinese Institute of Industrial Engineers
Volume14
Issue number4
DOIs
StatePublished - 1 Jan 1997

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