Titlebook: Risk Analysis of Complex and Uncertain Systems; Louis Anthony Cox Book 2009 Springer-Verlag US 2009 Risk Assessment.Risk Management.causal

PANG

黑豹

jagged

不怕任性

Determining What Can Be Predicted: Identifiabilityed for business, engineering, biological, social, and economic systems. (Agent-based simulation models have also been developed for complex social and economic systems, but this chapter focuses on continuous simulation.)

LARK

Value of Information (VOI) in Risk Management Policies for Tracking and Testing Imported Cattle for ncertain, and potentially nonlinear systems include the following:. (Chapters 6 and 7) for identifying potential causal relations (including nonlinear and multivariate ones with high-order interactions) in large multivariate data sets.

Suggestions

Overcoming Preconceptions and Confirmation Biases Using Data Miningeither supporting them by showing that they are consistent with data, or refuting them by showing that they are not. In the latter case, data-mining and modeling methods can also suggest improved causal hypotheses.

Infuriate

Confronting Uncertain Causal Mechanisms – Portfolios of Possibilitieses of carcinogenic action. Not enough is known about how cadmium affects lung cancer to allow useful bounds on risk to be established using biomarkers, as in Chapter 8. A different strategy is needed for QRA.

HAIRY

搏斗

Improving Antiterrorism Risk Analysisamong its components, the nonadditivity of risks estimated using the formula, its inability to use risk-scoring results to allocate defensive resources optimally, and the intrinsic subjectivity and ambiguity of the ., ., and . numbers.

PANG

Quantitative Risk Assessment Goals and Challengests advocate quantitative risk assessment (QRA) as providing both a logical framework and a systematic procedure for organizing and applying scientific and engineering knowledge to improve “rational” (consequence-driven) decision making when the consequences of alternative decisions are uncertain. It