摘要：This issue will introduce the research object and keyword definitions of the intensively read replica paper "Crowd intelligence kn
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今天小编为您带来“越览（138）——精读期刊论文
《Multi-criteria decision support
and uncertainty handling, propagation and
visualisation for emergency and
remediation management》的
研究对象和关键词定义”。
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Today, the editor brings the
＂Yue Lan (138)：Intensive reading of the journal article
＇Multi-criteria decision support
and uncertainty handling, propagation and
visualisation for emergency and
remediation management’
research object and keyword definition".
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一、内容摘要（Summary of Content）
本期推文将从思维导图、精读内容、知识补充三个方面介绍精读复刻论文《基于共词网络的群智知识挖掘方法——在应急决策中应用》研究对象和关键词定义。
This issue will introduce the research object and keyword definitions of the intensively read replica paper "Crowd intelligence knowledge mining method based on co-word network – application in emergency decision-making" in terms of mind maps, intensively read content, and knowledge supplementation.
二、思维导图（Mind Mapping）
三、精读内容（Intensive reading content）
（一）研究对象——针对核或放射性紧急情况管理中的决策支持系统（Research object—Decision support systems in nuclear or radiological emergency management）
本文的研究对象是针对核或放射性紧急情况管理中的决策支持系统，特别是如何在决策过程中处理、传播以及可视化不确定性。具体来说，研究引入了蒙特卡洛方法以在实时在线决策支持系统（RODOS）中对不确定性进行一致性建模和传播，并通过Web-HIPRE工具实现这些不确定性的可视化和沟通，从而为应急管理和补救措施评估提供透明且全面的决策支持。这包括对长期措施的效果进行评估，同时考虑到决策团队的偏好，以及通过有效的可视化手段帮助理解和区分不同应急响应策略之间的潜在结果和不确定性。
The research object of this paper is the decision support system in nuclear or radiological emergency management, especially how to handle, propagate and visualize uncertainty in the decision-making process. Specifically, the study introduces Monte Carlo methods to model and propagate uncertainties consistently in the real-time online decision support system (RODOS), and visualizes and communicates these uncertainties through the Web-HIPRE tool, so as to provide transparent and comprehensive decision support for emergency management and remedial measures evaluation. This includes the evaluation of the effects of long-term measures, taking into account the preferences of the decision-making team, and helping to understand and distinguish the potential results and uncertainties between different emergency response strategies through effective visualization.
（二）关键词定义（Keyword definition）
1. RODOS系统（RODOS System）
RODOS是一个为欧洲范围内的核事故或放射性紧急事件开发的实时在线决策支持系统，旨在为各级政府和应急响应人员提供统一、系统化的决策依据。该系统包含多个子系统模块：包括用于模拟污染扩散的“分析子系统”，评估对策后果的“对策子系统”，以及集成 Web-HIPRE 的“评估子系统”，从而实现从数据监测、后果预测到多方案评价的一体化支持。
RODOS is a real-time online decision support system developed for nuclear accidents or radiological emergencies in Europe, aiming to provide a unified and systematic basis for decision-making for governments at all levels and emergency responders. The system consists of multiple subsystem modules: including an "analysis subsystem" for simulating the spread of contamination, a "countermeasures subsystem" for evaluating the consequences of countermeasures, and an "evaluation subsystem" that integrates Web-HIPRE, thereby achieving integrated support from data monitoring, consequence prediction to multi-scenario evaluation.
2.多准则决策分析（MCDA）（Multi-criteria decision analysis）
多准则决策分析是一种用于结构化处理复杂决策问题的方法，尤其适用于涉及多个评估标准和多方利益相关者的场景。本文中，MCDA 被用于在核紧急管理中，对各种补救措施（如食品处理、饲料更换、处置方式等）进行系统性评价，综合考虑放射效应、资源消耗、社会接受度等多个标准，并结合专家或决策小组的偏好权重做出最终判断。
Multi-criteria decision analysis is a method for structured processing of complex decision problems, especially for scenarios involving multiple evaluation criteria and multiple stakeholders. In this paper, MCDA is used to systematically evaluate various remedial measures (such as food treatment, feed replacement, disposal methods, etc.) in nuclear emergency management, taking into account multiple criteria such as radiation effects, resource consumption, and social acceptance, and combining the preference weights of experts or decision-making groups to make final judgments.
3.不确定性建模与传播（Uncertainty modeling and propagation）
该术语指的是对影响决策分析过程的输入数据或模型参数的不确定性进行量化、模拟和分析的过程。在本文中，不确定性来自于多个方面，如放射源项的释放量、风向变化等，作者采用统计分布（如对数正态、正态分布）对这些变量进行建模，并利用蒙特卡洛方法将这些不确定性通过 RODOS 系统的各个子模块进行传播，最终影响到对补救策略的综合评估。
The term refers to the process of quantifying, simulating, and analyzing the uncertainty of input data or model parameters that affect the decision-making analysis process. In this paper, the uncertainty comes from multiple aspects, such as the release of radioactive source items, wind direction changes, etc. The author uses statistical distributions (such as lognormal and normal distribution) to model these variables and uses the Monte Carlo method to propagate these uncertainties through the various submodules of the RODOS system, ultimately affecting the comprehensive evaluation of the remediation strategy.
4.蒙特卡洛方法（Monte Carlo method）
蒙特卡洛方法是一种基于随机抽样与统计模拟的数值计算方法，用于估算系统中由于输入不确定性带来的输出变化范围。在本文中，蒙特卡洛方法被用于在 RODOS 系统中对输入变量（如源项和气象条件）进行随机采样，然后在多个并行模拟中运行系统流程，从而得到每种补救策略在不同情景下的表现。这为不确定性传播和结果可视化提供了基础。
The Monte Carlo method is a numerical calculation method based on random sampling and statistical simulation, which is used to estimate the range of output variations caused by input uncertainty in the system. In this paper, the Monte Carlo method is used to randomly sample input variables (such as source terms and meteorological conditions) in the RODOS system, and then run the system process in multiple parallel simulations to obtain the performance of each remediation strategy under different scenarios. This provides a basis for uncertainty propagation and result visualization.
5.可视化与敏感性分析（Visualization and sensitivity analysis）
这一关键词指的是将决策分析结果中蕴含的不确定性信息以直观图形方式展示，并评估系统对关键参数变化的响应程度。在本文中，研究者采用堆叠柱状图等形式展示“最有可能场景”、“最佳场景（95%分位）”和“最差场景（5%分位）”下的评价结果，同时进行权重参数的敏感性分析，以判断不同补救策略在各种条件下的稳定性和可区分性，帮助决策者理解和权衡风险。
This keyword refers to the use of intuitive graphical representations of the uncertainty information contained in the decision analysis results, and the evaluation of the system's response to changes in key parameters. In this paper, the researchers used stacked bar charts and other forms to display the evaluation results under the "most likely scenario", "best scenario (95% percentile)" and "worst scenario (5% percentile)", and conducted sensitivity analysis of weight parameters to determine the stability and distinguishability of different remediation strategies under various conditions, helping decision makers understand and weigh risks.
四、知识补充（Knowledge supplement）
Web-HIPRE（Hierarchical Preference Analysis）是一种基于浏览器运行的图形化决策支持工具，用于处理结构复杂、标准众多、参与者意见多样的决策问题。它诞生于芬兰赫尔辛基工业大学系统分析实验室，由 Mustajoki 和 Hämäläinen 等人开发，旨在为政府、研究机构、企业或危机管理部门提供结构化、多维度的决策建模与评估平台。
Web-HIPRE (Hierarchical Preference Analysis) is a browser-based graphical decision support tool for dealing with decision problems with complex structures, multiple criteria, and diverse opinions of participants. It was born in the System Analysis Laboratory of the Helsinki University of Technology in Finland and was developed by Mustajoki, Hämäläinen and others. It aims to provide a structured, multi-dimensional decision modeling and evaluation platform for governments, research institutions, enterprises or crisis management departments.
Web-HIPRE的核心功能是将一个多目标、多方案的复杂决策问题通过“准则层次结构”分解，使用户可以逐层分析各决策因素的相对重要性与影响力，并最终综合形成明确的决策建议或排序。
The core function of Web-HIPRE is to decompose a complex decision-making problem with multiple objectives and multiple options through a "criteria hierarchy", allowing users to analyze the relative importance and influence of each decision factor layer by layer, and finally comprehensively form clear decision recommendations or rankings.
Web-HIPRE建立在两种经典多准则决策理论之上：
Web-HIPRE is built on two classical multi-criteria decision-making theories:
1. MAVT（Multi-Attribute Value Theory）
多属性价值理论侧重于为每个准则建立独立的价值函数，并通过线性加权求和得出每个选项的综合价值。在 MAVT 中，每个准则和子准则的权重（反映其重要性）由用户赋值确定，适合于定量数据丰富或用户能明确表达偏好的场景。
Multi-attribute value theory focuses on establishing an independent value function for each criterion and deriving the comprehensive value of each option through linear weighted summation. In MAVT, the weight of each criterion and sub-criterion (reflecting its importance) is determined by the user's assignment, which is suitable for scenarios with abundant quantitative data or where users can clearly express their preferences.
2. AHP（Analytic Hierarchy Process）
层次分析法是 Thomas Saaty 提出的经典方法，强调成对比较准则和选项的相对重要性，以此推导出一致性的权重分配结果。适用于用户偏好难以用绝对数值表达时，采用相对判断进行权重推导。
The analytic hierarchy process is a classic method proposed by Thomas Saaty, which emphasizes the relative importance of pairwise comparison criteria and options to derive consistent weight distribution results. It is suitable for using relative judgment to derive weights when user preferences are difficult to express in absolute numbers.
Web-HIPRE允许用户在 MAVT 与 AHP 模式之间灵活切换，满足不同决策风格与信息背景的需要。
Web-HIPRE allows users to flexibly switch between MAVT and AHP modes to meet the needs of different decision-making styles and information backgrounds.
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翻译：谷歌翻译
参考资料：百度百科、Chat GPT
参考文献： Jutta Geldermann, Valentin Bertsch, Otto Rentz. Multi-criteria decision support and uncertainty handling, propagation and visualisation for emergency and remediation management [J]. Operations Research, 2006, 1(1): 755-760.
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