A new health prediction model for a sensor network based on belief rule base with attribute reliability

Abstract Health prediction plays an essential role in improving the reliability of a sensor network by guiding the network maintenance. However, affected by interference factors in the real operational environment, the reliability of the monitoring information about the sensor network tends to decli...

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Autores principales:	Shaohua Li, Jingying Feng, Wei He, Ruihua Qi, He Guo
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/7482b99e33334c46b9057616c426991c
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spelling	oai:doaj.org-article:7482b99e33334c46b9057616c426991c2021-12-02T14:06:49ZA new health prediction model for a sensor network based on belief rule base with attribute reliability10.1038/s41598-021-82594-62045-2322https://doaj.org/article/7482b99e33334c46b9057616c426991c2021-02-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-82594-6https://doaj.org/toc/2045-2322Abstract Health prediction plays an essential role in improving the reliability of a sensor network by guiding the network maintenance. However, affected by interference factors in the real operational environment, the reliability of the monitoring information about the sensor network tends to decline, which affects the health prediction accuracy. Furthermore, the lack of monitoring information and high complexity of the network increase the difficulty of health prediction. To solve these three problems, this paper proposes a new sensor network health prediction model based on the belief rule base model with attribute reliability (BRB-r). The BRB-r model is an expert system that fully considers the qualitative knowledge and quantitative data of the sensor network. In addition, it can address the fuzziness and nondeterminacy of this qualitative knowledge. In the new model, the unreliable monitoring information of the sensor network is handled by the attribute reliability mechanism. The reliability of the sensor is calculated by the average distance method. Due to the effect of the fuzziness and nondeterminacy of expert knowledge, the health status of the sensor network cannot be accurately estimated by the initial health prediction model. Consequently, the optimization model for the health prediction model is established. Finally, a case study regarding a sensor network for oil storage tanks is conducted, and the validity of this method is demonstrated.Shaohua LiJingying FengWei HeRuihua QiHe GuoNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-10 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Shaohua Li Jingying Feng Wei He Ruihua Qi He Guo A new health prediction model for a sensor network based on belief rule base with attribute reliability
description	Abstract Health prediction plays an essential role in improving the reliability of a sensor network by guiding the network maintenance. However, affected by interference factors in the real operational environment, the reliability of the monitoring information about the sensor network tends to decline, which affects the health prediction accuracy. Furthermore, the lack of monitoring information and high complexity of the network increase the difficulty of health prediction. To solve these three problems, this paper proposes a new sensor network health prediction model based on the belief rule base model with attribute reliability (BRB-r). The BRB-r model is an expert system that fully considers the qualitative knowledge and quantitative data of the sensor network. In addition, it can address the fuzziness and nondeterminacy of this qualitative knowledge. In the new model, the unreliable monitoring information of the sensor network is handled by the attribute reliability mechanism. The reliability of the sensor is calculated by the average distance method. Due to the effect of the fuzziness and nondeterminacy of expert knowledge, the health status of the sensor network cannot be accurately estimated by the initial health prediction model. Consequently, the optimization model for the health prediction model is established. Finally, a case study regarding a sensor network for oil storage tanks is conducted, and the validity of this method is demonstrated.
format	article
author	Shaohua Li Jingying Feng Wei He Ruihua Qi He Guo
author_facet	Shaohua Li Jingying Feng Wei He Ruihua Qi He Guo
author_sort	Shaohua Li
title	A new health prediction model for a sensor network based on belief rule base with attribute reliability
title_short	A new health prediction model for a sensor network based on belief rule base with attribute reliability
title_full	A new health prediction model for a sensor network based on belief rule base with attribute reliability
title_fullStr	A new health prediction model for a sensor network based on belief rule base with attribute reliability
title_full_unstemmed	A new health prediction model for a sensor network based on belief rule base with attribute reliability
title_sort	new health prediction model for a sensor network based on belief rule base with attribute reliability
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/7482b99e33334c46b9057616c426991c
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A new health prediction model for a sensor network based on belief rule base with attribute reliability

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