Approach to Integrate Fuzzy Fault Tree with Bayesian Network

Dynamic Safety Analysis CNG Stations Using Fault Tree Approach and Bayesian Network

Introduction: The safety of CNG stations is important because of their location in urban areas, as well as to prevent accidents and to protect the safety of personnel, property, and environment. An event occurrence analysis with probability updating is the key to dynamic safety analysis. Methods and materials: In this study, the Failure Modes and Effects Analysis (FMEA) technique was used to d...

Subcutaneous Glucose Biosensor Failure – a Fuzzy Fault Tree Analysis Approach

Diabetes mellitus is a disease of major global importance, increasing in frequency at almost epidemic rates. In order to optimize diabetes management and, therefore, reduce hyperor hypo-glycaemia complications, continuous and reliable in vivo (subcutaneous or intravenous) glucose monitoring is indispensable. To that end, subcutaneous sensors have progressed more rapidly as they can be linked to...

Uncertainty in fault tree analysis: A fuzzy approach

Fuzzy fault tree analysis: revisited

This talk will review two case studies that examine the effectiveness of using Fuzzy Top Event Probability (FTEP) over the conventional approach. Case study one relates to flash vessel in an ammonia tank, while in case study two ,using fuzzy set theory, the FTEP has been estimated for the existing ammonia storage tank in a large fertilizer complex located in Mumbai, India. In addition, a new fo...

Bayesian network data imputation with application to survival tree analysis

Retrospective clinical datasets are often characterized by a relatively small sample size and many missing data. In this case, a common way for handling the missingness consists in discarding from the analysis patients with missing covariates, further reducing the sample size. Alternatively, if the mechanism that generated the missing allows, incomplete data can be imputed on the basis of the o...