Add to ORKGThis paper concerns different frameworks for the uncertainty representation as tools for representing and handling data in safety studies. We consider three main theories, namely: Bayesian probability theory, Shafer--Dempster theory of evidence (Shafer 1976) and Zadeh possibility theory (Zadeh 1978) as alternative frameworks for the data representation
Uncertainty in situations involving risk is frequently modelled by assuming a plausible form of prob...
International audienceQuantitative risk analysis (QRA) is a fundamental part of the decision-making ...
International audienceThis article tries to clarify the potential role to be played by uncertainty t...
International audienceIn Nuclear Power Plants, Probabilistic Risk Assessment (PRA) insights contribu...
International audienceExplores methods for the representation and treatment of uncertainty in risk a...
This paper compares Evidence Theory (ET) and Bayesian Theory (BT) for uncertainty modeling and decis...
This paper discusses the challenges involved in the representation and treatment of uncertainties in...
International audienceDue to its major focus on knowledge representation and reasoning, artificial i...
International audienceThis chapter completes the survey of the existing frameworks for representing ...
An important issue in risk analysis is the distinction between epistemic and aleatory uncertainties....
International audienceModels for the assessment of the risk of complex engineering systems are affec...
International audienceIn nuclear power plants, probabilistic risk assessment insights contribute to ...
Application of the Bayes' formula leaves little room for representation of ignorance and vagueness i...
A risk-informed regulatory approach implies that risk insights be used as supplement of deterministi...
AbstractThis paper compares four measures that have been advocated as models for uncertainty in expe...
Uncertainty in situations involving risk is frequently modelled by assuming a plausible form of prob...
International audienceQuantitative risk analysis (QRA) is a fundamental part of the decision-making ...
International audienceThis article tries to clarify the potential role to be played by uncertainty t...
International audienceIn Nuclear Power Plants, Probabilistic Risk Assessment (PRA) insights contribu...
International audienceExplores methods for the representation and treatment of uncertainty in risk a...
This paper compares Evidence Theory (ET) and Bayesian Theory (BT) for uncertainty modeling and decis...
This paper discusses the challenges involved in the representation and treatment of uncertainties in...
International audienceDue to its major focus on knowledge representation and reasoning, artificial i...
International audienceThis chapter completes the survey of the existing frameworks for representing ...
An important issue in risk analysis is the distinction between epistemic and aleatory uncertainties....
International audienceModels for the assessment of the risk of complex engineering systems are affec...
International audienceIn nuclear power plants, probabilistic risk assessment insights contribute to ...
Application of the Bayes' formula leaves little room for representation of ignorance and vagueness i...
A risk-informed regulatory approach implies that risk insights be used as supplement of deterministi...
AbstractThis paper compares four measures that have been advocated as models for uncertainty in expe...
Uncertainty in situations involving risk is frequently modelled by assuming a plausible form of prob...
International audienceQuantitative risk analysis (QRA) is a fundamental part of the decision-making ...
International audienceThis article tries to clarify the potential role to be played by uncertainty t...