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A network is an abstract structure capturing only the basics of connection patterns and little else. Because it is a generalized pattern, tools developed for analyzing, modeling and understanding networks can theoretically be implemented across disciplines. As long as a system can be represented by a network, there is an extensive set of tools – mathematical, computational, and statistical – that are well-developed and if understood can be applied to the analysis of the system of interest. Tools that are currently employed in risk assessment are often sufficient, but model complexity and limitations of computational power can tether risk assessors to involve more causal connections and account for more Black Swan event outcomes. By applying network theory tools to risk assessment, computational limitations may be overcome and result in broader coverage of events with a narrowed range of uncertainties.〔Newman, Mark E. J. ''Networks: an Introduction''. Oxford: Oxford UP, 2010. p.2〕 Decision-making processes are not incorporated into routine risk assessments; however, they play a critical role in such processes.〔National Research Council (NRC). ''Red Book Paradigm''. Risk Assessment in the Federal Government: Understanding the Process. Washington D.C.: National Academy Press, 1983.〕 It is therefore very important for risk assessors to minimize confirmation bias by carrying out their analysis and publishing their results with minimal involvement of external factors such as politics, media, and advocates. In reality, however, it is nearly impossible to break the iron triangle among politicians, scientists (in this case, risk assessors), and advocates and media.〔Pielke Jr., Roger A. ''Policy, Politics and Perspective.'' Nature 416 (2002): 367-68.〕 Risk assessors need to be sensitive to the difference between risk studies and risk perceptions.〔Slovic, Paul. ''Perception of Risk.'' Science 236 (1987): 280-85.〕〔National Research Council (NRC). ''Orange Book Paradigm''. Understanding Risk: Informing Decisions in a Democratic Society. Washington D.C.: National Academy Press, 1996.〕 One way to bring the two closer is to provide decision-makers with data they can easily rely on and understand. Employing networks in the risk analysis process can visualize causal relationships and identify heavily-weighted or important contributors to the probability of the critical event.〔Rausand, Marvin. ''Risk Assessment: Theory, Methods, and Applications''. Hoboken, NJ: John Wiley & Sons, 2011. p.295.〕 A "bow-tie" diagram, cause-and-effect diagram, Bayesian network (a ''directed acyclic'' network) and fault trees are few examples of how network theories can be applied in risk assessment.〔Rausand, Marvin. ''Risk Assessment: Theory, Methods, and Applications''. Hoboken, NJ: John Wiley & Sons, 2011. p.266-302.〕 In epidemiology risk assessments (Figure 7 and 9), once a network model was constructed, we can visually see then quantify and evaluate the potential exposure or infection risk of people related to the well-connected patients (Patient 1, 6, 35, 130 and 127 in Figure 7) or high-traffic places (Hotel M in Figure 9). In ecological risk assessments (Figure 8), through a network model we can identify the keystone species and determine how widespread the impacts will extend from the potential hazards being investigated. ==Risk assessment key components== (詳細は# Plan and prepare the risk analysis. # Define and delimit the system and the scope of the analysis. # Identify hazards and potential hazardous events. # Determine causes and frequency of each hazardous event. # Identify accident scenarios (i.e. even sequences) that may be initiated by each hazardous event. # Select relevant and typical accident scenarios. # Determine the consequences of each accident scenario. # Determine the frequency of each accident scenario. # Assess the uncertainty. # Establish and describe the risk picture. # Report the analysis. # Evaluate the risk against risk acceptance criteria # Suggest and evaluate potential risk-reducing measures. Naturally, the number of steps required varies with each assessment. It depends on the scope of the analysis and the complexity of the study object.〔Rausand, Marvin. ''Risk Assessment: Theory, Methods, and Applications''. Hoboken, NJ: John Wiley & Sons, 2011. p.124.〕 Because these is always varies degrees of uncertainty involved in any risk analysis process, sensitivity and uncertainty analysis are usually carried out to mitigate the level of uncertainty and therefore improve the overall risk assessment result. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Network theory in risk assessment」の詳細全文を読む スポンサード リンク
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