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A Bayesian Failure Prediction Network Based on Text Sequence Mining and Clustering

The purpose of this paper is to predict failures based on textual sequence data. The current failure prediction is mainly based on structured data. However, there are many unstructured data in aircraft maintenance. The failure mentioned here refers to failure types, such as transmitter failure and s...

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Detalles Bibliográficos
Autores principales: Chang, Wenbing, Xu, Zhenzhong, You, Meng, Zhou, Shenghan, Xiao, Yiyong, Cheng, Yang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7512510/
https://www.ncbi.nlm.nih.gov/pubmed/33266647
http://dx.doi.org/10.3390/e20120923
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author Chang, Wenbing
Xu, Zhenzhong
You, Meng
Zhou, Shenghan
Xiao, Yiyong
Cheng, Yang
author_facet Chang, Wenbing
Xu, Zhenzhong
You, Meng
Zhou, Shenghan
Xiao, Yiyong
Cheng, Yang
author_sort Chang, Wenbing
collection PubMed
description The purpose of this paper is to predict failures based on textual sequence data. The current failure prediction is mainly based on structured data. However, there are many unstructured data in aircraft maintenance. The failure mentioned here refers to failure types, such as transmitter failure and signal failure, which are classified by the clustering algorithm based on the failure text. For the failure text, this paper uses the natural language processing technology. Firstly, segmentation and the removal of stop words for Chinese failure text data is performed. The study applies the word2vec moving distance model to obtain the failure occurrence sequence for failure texts collected in a fixed period of time. According to the distance, a clustering algorithm is used to obtain a typical number of fault types. Secondly, the failure occurrence sequence is mined using sequence mining algorithms, such as-PrefixSpan. Finally, the above failure sequence is used to train the Bayesian failure network model. The final experimental results show that the Bayesian failure network has higher accuracy for failure prediction.
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spelling pubmed-75125102020-11-09 A Bayesian Failure Prediction Network Based on Text Sequence Mining and Clustering Chang, Wenbing Xu, Zhenzhong You, Meng Zhou, Shenghan Xiao, Yiyong Cheng, Yang Entropy (Basel) Article The purpose of this paper is to predict failures based on textual sequence data. The current failure prediction is mainly based on structured data. However, there are many unstructured data in aircraft maintenance. The failure mentioned here refers to failure types, such as transmitter failure and signal failure, which are classified by the clustering algorithm based on the failure text. For the failure text, this paper uses the natural language processing technology. Firstly, segmentation and the removal of stop words for Chinese failure text data is performed. The study applies the word2vec moving distance model to obtain the failure occurrence sequence for failure texts collected in a fixed period of time. According to the distance, a clustering algorithm is used to obtain a typical number of fault types. Secondly, the failure occurrence sequence is mined using sequence mining algorithms, such as-PrefixSpan. Finally, the above failure sequence is used to train the Bayesian failure network model. The final experimental results show that the Bayesian failure network has higher accuracy for failure prediction. MDPI 2018-12-03 /pmc/articles/PMC7512510/ /pubmed/33266647 http://dx.doi.org/10.3390/e20120923 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Chang, Wenbing
Xu, Zhenzhong
You, Meng
Zhou, Shenghan
Xiao, Yiyong
Cheng, Yang
A Bayesian Failure Prediction Network Based on Text Sequence Mining and Clustering
title A Bayesian Failure Prediction Network Based on Text Sequence Mining and Clustering
title_full A Bayesian Failure Prediction Network Based on Text Sequence Mining and Clustering
title_fullStr A Bayesian Failure Prediction Network Based on Text Sequence Mining and Clustering
title_full_unstemmed A Bayesian Failure Prediction Network Based on Text Sequence Mining and Clustering
title_short A Bayesian Failure Prediction Network Based on Text Sequence Mining and Clustering
title_sort bayesian failure prediction network based on text sequence mining and clustering
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7512510/
https://www.ncbi.nlm.nih.gov/pubmed/33266647
http://dx.doi.org/10.3390/e20120923
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