Dynamic risk analysis with alarm data to improve process safety using Bayesian network

2014 ◽  
Author(s):  
Jianfeng Zhu ◽  
Jinsong Zhao ◽  
Fan Yang
Keyword(s):  
Risk Analysis ◽  
Bayesian Network ◽  
Process Safety ◽  
Dynamic Risk

Dynamic risk analysis of offloading process in floating liquefied natural gas (FLNG) platform using Bayesian Network

2016 ◽  
Vol 41 ◽  
pp. 259-269 ◽  
Author(s):  
ChuiTing Yeo ◽  
Jyoti Bhandari ◽  
Rouzbeh Abbassi ◽  
Vikram Garaniya ◽  
Shuhong Chai ◽  
...  
Keyword(s):  
Natural Gas ◽  
Risk Analysis ◽  
Bayesian Network ◽  
Liquefied Natural Gas ◽  
Dynamic Risk

Dynamic risk analysis using alarm databases to improve process safety and product quality: Part II-Bayesian analysis

AIChE Journal ◽  
2011 ◽  
Vol 58 (3) ◽  
pp. 826-841 ◽  
Author(s):  
Ankur Pariyani ◽  
Warren D. Seider ◽  
Ulku G. Oktem ◽  
Masoud Soroush
Keyword(s):  
Risk Analysis ◽  
Bayesian Analysis ◽  
Product Quality ◽  
Process Safety ◽  
Dynamic Risk ◽  
Alarm Databases

Dynamic risk analysis using alarm databases to improve process safety and product quality: Part I-Data compaction

AIChE Journal ◽  
2011 ◽  
Vol 58 (3) ◽  
pp. 812-825 ◽  
Author(s):  
Ankur Pariyani ◽  
Warren D. Seider ◽  
Ulku G. Oktem ◽  
Masoud Soroush
Keyword(s):  
Risk Analysis ◽  
Product Quality ◽  
Process Safety ◽  
Dynamic Risk ◽  
Data Compaction ◽  
Alarm Databases

Dynamic risk analysis for adjacent buildings in tunneling environments: a Bayesian network based approach

2015 ◽  
Vol 29 (5) ◽  
pp. 1447-1461 ◽  
Author(s):  
Xianguo Wu ◽  
Zhou Jiang ◽  
Limao Zhang ◽  
Miroslaw J. Skibniewski ◽  
Jingbing Zhong
Keyword(s):  
Risk Analysis ◽  
Bayesian Network ◽  
Dynamic Risk ◽  
Adjacent Buildings

A Bayesian-Network-based Approach to Risk Analysis in Runway Excursions

2019 ◽  
Vol 72 (5) ◽  
pp. 1121-1139 ◽  
Author(s):  
Fernando Calle-Alonso ◽  
Carlos J. Pérez ◽  
Eduardo S. Ayra
Keyword(s):  
Risk Analysis ◽  
Bayesian Network ◽  
Exploratory Analysis ◽  
Hypothesis Tests ◽  
Aircraft Accidents ◽  
Risk Scenarios ◽  
Key Variables ◽  
Expert Recommendations

Aircraft accidents are extremely rare in the aviation sector. However, their consequences can be very dramatic. One of the most important problems is runway excursions, when an aircraft exceeds the end (overrun) or the side (veer-off) of the runway. After performing exploratory analysis and hypothesis tests, a Bayesian-network-based approach was considered to provide information from risk scenarios involving landing procedures. The method was applied to a real database containing key variables related to landing operations on three runways. The objective was to analyse the effects over runway overrun excursions of failing to fulfil expert recommendations upon landing. For this purpose, the most influential variables were analysed statistically, and several scenarios were built, leading to a runway ranking based on the risk assessed.

Fuzzy-support vector machine geotechnical risk analysis method based on Bayesian network

2019 ◽  
Vol 16 (8) ◽  
pp. 1975-1985 ◽  
Author(s):  
Yang Liu ◽  
Jian-jing Zhang ◽  
Chong-hao Zhu ◽  
Bo Xiang ◽  
Dong Wang
Keyword(s):  
Support Vector Machine ◽  
Risk Analysis ◽  
Bayesian Network ◽  
Support Vector ◽  
Analysis Method ◽  
Fuzzy Support Vector Machine ◽  
Geotechnical Risk
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