relation: https://khub.utp.edu.my/scholars/11331/
title: Predictive analytics for machine failure using optimized recurrent neural network-gated recurrent unit (GRU)
creator: Zainuddin, Z.
creator: P Akhir, E.A.
creator: Aziz, N.
description: This paper proposed a technique named Recurrent Neural Network-Gated Recurrent Unit (RNN-GRU) to predict the condition of machines by using time series data generated by oil and gas company. The problem raised due to limited research of RNN-GRU in improving the accuracy through hyperparameter tuning. Hence, this paper will provide an optimization method that can improve the accuracy of RNN-GRU in forecasting time series data. The preliminary findings of the experiment conducted shows that RNN-GRU can utilize time series data to predict machine failure with improved high accuracy. © 2019 IEEE.
publisher: Institute of Electrical and Electronics Engineers Inc.
date: 2019
type: Conference or Workshop Item
type: PeerReviewed
identifier:   Zainuddin, Z. and P Akhir, E.A. and Aziz, N.  (2019) Predictive analytics for machine failure using optimized recurrent neural network-gated recurrent unit (GRU).  In: UNSPECIFIED.     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85079346213&doi=10.1109%2fAiDAS47888.2019.8970725&partnerID=40&md5=ac076132c400990b24e1c17a4bc8214c
relation: 10.1109/AiDAS47888.2019.8970725
identifier: 10.1109/AiDAS47888.2019.8970725