Seepage behavior assessment of earth-rock dams based on Bayesian network

Seepage behavior assessment is an important part of the safety operation assessment of earth-rock dams, because of insufficient intelligent analysis of monitoring information, abnormal phenomena or measured values are often ignored or improperly processed. To improve the intelligent performance of t...

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Autores principales:	Lu He, Shijun Wang, Yanchang Gu, Qiong Pang, Yunxing Wu, Jiefa Ding, Jihao Yan
Formato:	article
Lenguaje:	EN
Publicado:	SAGE Publishing 2021
Materias:	Electronic computers. Computer science QA75.5-76.95
Acceso en línea:	https://doaj.org/article/ef268a6dde9747a59412af2351c7318f
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id	oai:doaj.org-article:ef268a6dde9747a59412af2351c7318f
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spelling	oai:doaj.org-article:ef268a6dde9747a59412af2351c7318f2021-12-02T08:05:24ZSeepage behavior assessment of earth-rock dams based on Bayesian network1550-147710.1177/15501477211058672https://doaj.org/article/ef268a6dde9747a59412af2351c7318f2021-12-01T00:00:00Zhttps://doi.org/10.1177/15501477211058672https://doaj.org/toc/1550-1477Seepage behavior assessment is an important part of the safety operation assessment of earth-rock dams, because of insufficient intelligent analysis of monitoring information, abnormal phenomena or measured values are often ignored or improperly processed. To improve the intelligent performance of the monitoring system, this article has established an assessment framework covering project quality, maintenance status, monitoring data analysis, and on-site inspection based on the relevant norms of seepage safety assessment of earth-rock dams and the expert survey scoring method, and the Leaky Noisy-OR Gate extended model were used to determine the probability of events, and the dynamic and static Bayesian networks used to assess the possibility of seepage failure of earth-rock dams and diagnose the most likely cause of failure. The function of static and dynamic Bayesian networks to assess the seepage behavior of earth-rock dams, abnormal measured values, and causes of anomalies can make up for the limitations of reservoir management personnel and monitoring system in seepage failure experience and seepage knowledge of earth-rock dams and enable better handling of abnormal phenomena and monitoring information, making the monitoring system more intelligent.Lu HeShijun WangYanchang GuQiong PangYunxing WuJiefa DingJihao YanSAGE PublishingarticleElectronic computers. Computer scienceQA75.5-76.95ENInternational Journal of Distributed Sensor Networks, Vol 17 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Electronic computers. Computer science QA75.5-76.95
spellingShingle	Electronic computers. Computer science QA75.5-76.95 Lu He Shijun Wang Yanchang Gu Qiong Pang Yunxing Wu Jiefa Ding Jihao Yan Seepage behavior assessment of earth-rock dams based on Bayesian network
description	Seepage behavior assessment is an important part of the safety operation assessment of earth-rock dams, because of insufficient intelligent analysis of monitoring information, abnormal phenomena or measured values are often ignored or improperly processed. To improve the intelligent performance of the monitoring system, this article has established an assessment framework covering project quality, maintenance status, monitoring data analysis, and on-site inspection based on the relevant norms of seepage safety assessment of earth-rock dams and the expert survey scoring method, and the Leaky Noisy-OR Gate extended model were used to determine the probability of events, and the dynamic and static Bayesian networks used to assess the possibility of seepage failure of earth-rock dams and diagnose the most likely cause of failure. The function of static and dynamic Bayesian networks to assess the seepage behavior of earth-rock dams, abnormal measured values, and causes of anomalies can make up for the limitations of reservoir management personnel and monitoring system in seepage failure experience and seepage knowledge of earth-rock dams and enable better handling of abnormal phenomena and monitoring information, making the monitoring system more intelligent.
format	article
author	Lu He Shijun Wang Yanchang Gu Qiong Pang Yunxing Wu Jiefa Ding Jihao Yan
author_facet	Lu He Shijun Wang Yanchang Gu Qiong Pang Yunxing Wu Jiefa Ding Jihao Yan
author_sort	Lu He
title	Seepage behavior assessment of earth-rock dams based on Bayesian network
title_short	Seepage behavior assessment of earth-rock dams based on Bayesian network
title_full	Seepage behavior assessment of earth-rock dams based on Bayesian network
title_fullStr	Seepage behavior assessment of earth-rock dams based on Bayesian network
title_full_unstemmed	Seepage behavior assessment of earth-rock dams based on Bayesian network
title_sort	seepage behavior assessment of earth-rock dams based on bayesian network
publisher	SAGE Publishing
publishDate	2021
url	https://doaj.org/article/ef268a6dde9747a59412af2351c7318f
work_keys_str_mv	AT luhe seepagebehaviorassessmentofearthrockdamsbasedonbayesiannetwork AT shijunwang seepagebehaviorassessmentofearthrockdamsbasedonbayesiannetwork AT yanchanggu seepagebehaviorassessmentofearthrockdamsbasedonbayesiannetwork AT qiongpang seepagebehaviorassessmentofearthrockdamsbasedonbayesiannetwork AT yunxingwu seepagebehaviorassessmentofearthrockdamsbasedonbayesiannetwork AT jiefading seepagebehaviorassessmentofearthrockdamsbasedonbayesiannetwork AT jihaoyan seepagebehaviorassessmentofearthrockdamsbasedonbayesiannetwork
_version_	1718398699042766848

Seepage behavior assessment of earth-rock dams based on Bayesian network

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