Risk analysis and maintenance decision making of natural gas pipelines with external corrosion based on Bayesian network

Buried natural gas pipelines are vulnerable to external corrosion because they are encased in a soil environment for a long time.Identifying the causes of external corrosion and taking specific maintenance measures is essential.In this work,a risk analysis and maintenance decision-making model for natural gas pipelines with external corrosion is proposed based on a Bayesian network.A fault tree model is first employed to identify the causes of external corrosion.The Bayesian network for risk analysis is determined accordingly.The maintenance strategies are then inserted into the Bayesian network to show a reduction of the risk.The costs of maintenance strategies and the reduced risk after maintenance are combined in an optimization function to build a decision-making model.Because of the limitations of historical data,some of the parameters in the Bayesian network are obtained from a probabilistic estimation model,which combines expert experience and fuzzy set theory.Finally,a case study is carried out to verify the feasibility of the maintenance decision model.This indicates that the method proposed in this work can be used to provide effective maintenance schemes for different pipeline external corrosion scenarios and to reduce the possible losses caused by external corrosion.

A Risk-Based Multi-Criteria Decision Analysis Approach to Evaluating Transboundary Water Development—The Case of Lower Mekong River Basin

The Lower Mekong River basin (LMB) covers the lower part of the Mekong river basin, including Laos, Thailand, Cambodia and Vietnam. Due to numerous pressures from high population growth and intensive hydropower development, the LMB has been facing significant challenges concerning its biodiversity and ecosystem. In 2017, Mekong River Commission (MRC), an intergovernmental organisation founded in 1995 among LMB countries, established the Council Study, which analysed the impacts of water development scenarios concerning the environmental, socioeconomic aspects of the LMB. This paper explores the nature of risks to the LMB water development and subsequently evaluates LMB’s water development scenarios described in the Council Study by using a multi-criteria decision analysis (MCDA) method. MCDA method has been widely applied in the field of water resource management in order to assist the decision-making process by systematically evaluating a certain number of alternatives against well-selected criteria through a preference rating scheme. By implementing a risk-based comprehensive assessment of the LMB transboundary water, this study provides insights into the impacts of the increasing risks to the ecosystem and human beings on the water development of the basin over time, which assists to change the awareness and the perspective toward humans’ risks and transboundary river ecosystem of decision-makers. This paper provides valuable recommendations for MRC to improve their policy concerning benefit-sharing scheme, water planning and risk mitigation strategies.

Competence Set Analysis Under Risk and Uncertainty

The competence set analysis technology can be applied to solve the decision making problems successfully and satisfactorily. This paper mainly focuses on the expanding strategy research and development of the competence set under risk and uncertainty. A systematic expression of the competence set analysis is described, several expanding principles and strategies with regard to several different cases are presented, and their applications in the personnel training program are discussed, some conclusions and suggestions to be developed in a further work are included.

Uncertainty and Its Description in Decision Models

Various perspectives in uncertainty are briefly summarized in this paper, and the classification of uncertainties is discussed. The descriptions of different classes of uncertainty are also presented. Furthermore, a risk representation model for decision-making analysis is provided.

Study and Analysis of Chennai Flood 2015 Using GIS and Multicriteria Technique

Terrain characteristics of the land and meteorological properties of the region are the main natural factors for flood. The recent flood in Chennai was unexpected and not triggered by the above factors. Sometimes floods occur when the watershed size is considerably small which leads to the over flow of water inland may due to the encroachment and the urban development of the city. Temporarily used backwater effects in sewers and local drainage channels and creation of unsanitary conditions may cause flooding. Chennai flood was basically claimed to occur due to improper drainage system and underlying strata which was found to be landfill over the ponds and lakes. The Coouam River which flows through the centre of main city was found silting due to the improper drainage facilities and encroachment by the local peoples who causes flood. For the analysis of potentially affected areas Geographical Information System (GIS) integrated with Multicriteria Decision Analysis (MCDA) were employed. Ranking and displaying the potentially risky areas, the spatial Multicriteria analysis was used. It has been revealed that all most all the area’s having populations are likely to be exposed to flood hazard. At the end of study, a map of flood risk areas was generated and studied with a view to assisting decision makers on the consequences posed by the disaster.

Pricing Decision Support System for Generation Companies in Electricity Market

In order to meet the requirement of separating power plants from power network and that of the competition based power transaction in power market, the pricing decision support system for generation companies (GCPDSS) is built in electricity market. This paper introduces the conception of intelligent decision support system (IDSS) and puts emphasis on the systematical structural framework, work process, design principal, and fundamental function of GCPDSS. The system has the module to analyze the cost, to forecast the demand of power, to construct the pricing strategies, to manage the pricing risk, and to dispatch giving the pricing strategies. The case study illustrates that the friendly window-based user interface of the system enables the user to take full advantage of the capabilities of the system in order to make effective real-time decisions.

结合STPA和DEMATEL-ISM的民机起落架收放系统风险研究

为从系统整体角度完成对起落架收放系统的风险辨识和影响分析,将系统理论过程分析(Systematic Theory Process Analysis,STPA)与决策实验室分析-解释结构模型(Decision Making Trial and Evaluation Laboratory Interpretive Structural Modeling,DEMATEL-ISM)相结合来开展分析。首先,定义事故和系统级危险,以民机进近阶段放下起落架为例,运用STPA完成对风险因素的系统化辨识;其次,基于最大平均熵减(Maximum Mean De-entropy,MMDE)算法帮助DEMATEL-ISM模型确定阈值,完成对风险因素影响的重要性分析并识别可能引发系统级危险的风险传递路径,据此挖掘关键致因场景,以给出风险预防建议。结果显示:线路性能退化或失效、位置作动控制组件(Position Action Control Unit,PACU)核心处理器故障为关键原因因素,收放作动筒作动异常、机组成员操作不当、起落架指示灯显示异常、起落架液压选择阀作动异常、PACU信息接收有误为关键结果因素,这些因素均涉及多条可能引发系统级危险的风险传递路径,应予以重点控制。

2型糖尿病患者并发糖尿病肾病风险的列线图预测模型与验证研究

背景糖尿病肾病(DN)是糖尿病患者常见的并发症,对其发生风险进行预测与验证,有助于提前识别高风险患者并采取干预措施,以避免或延缓肾脏疾病的进展。目的分析影响2型糖尿病(T2DM)患者并发DN的风险因素,构建T2DM患者发生DN风险的预测模型并进行验证。方法选取2016年1月—2021年6月在新疆医科大学第一附属医院住院的5810例T2DM患者为研究对象,根据是否并发DN将患者分为DN组(481例)和非DN组(5329例)。对其中481例DN患者和非DN患者依据性别、年龄(±2岁)进行1∶1病例对照匹配,将匹配后的962例T2DM患者根据2∶1比例随机分为训练组(n=641)和验证组(n=321)。收集患者的基础数据,如临床特征、实验室检查结果及其他相关数据。采用LASSO回归优化筛选变量,利用多因素Logistic回归分析建立列线图预测模型。分别采用受试者工作特征(ROC)曲线、Hosmer-Lemeshow校准曲线和决策曲线分析(DCA)评价预测模型的区分度、校准度以及预测模型的临床有效性。结果DN组与非DN组患者性别、年龄、BMI、糖尿病病程、白细胞计数、总胆固醇、三酰甘油、低密度脂蛋白胆固醇、血清肌酐、高血压、收缩压、舒张压、糖化血红蛋白载脂蛋白B、24 h尿微量总蛋白、定性尿蛋白比较,差异有统计学意义(P<0.05)。采用LASSO回归分析方法,筛选出5个与T2DM患者发生DN风险相关的预测变量,结合多因素Logistic回归分析结果显示,糖尿病病程、总胆固醇、血清肌酐、高血压、定性尿蛋白是T2DM患者并发DN的危险因素(P<0.05)。训练组DN发生风险的ROC曲线下的面积(AUC)为0.866(95%CI=0.839~0.894),验证组DN发生风险的AUC为0.849(95%CI=0.804~0.889)。Hosmer-Lemeshow校准曲线拟合度较好(训练组P=0.748;验证组P=0.986)。DCA显示当患者的阈值概率为0.15~0.95时,使用列线图预测模型预测T2DM患者发生DN风险更有益。结论本研究发现糖尿病病程、总胆固醇、血清肌酐、高血压、定性尿蛋白可能是T2DM患者并发DN的危险因素,建立了包含该5个危险因素的列线图预测模型,可用于预测T2DM患者发生DN的风险。

融合专家领域知识和K-means聚类的三支风险评级方法

金融和医疗等实际环境中的决策关键在于决策风险的权衡考虑,准确预测和分类风险级别非常必要。然而,传统的群体决策关注专家评价意见的一致性和共识,对于获得客观的专家评价意见和决策质量的考虑较少,在风险评级场景中难以量化和评估决策实际效果。因此,引入数据驱动的思想,利用数据和聚类结果辅助发现专家评估意见,在三支决策理论框架下优化群体意见,改进和计算逻辑回归的判别点,并基于UCI和Kaggle的4个信贷风险和疾病诊断公开数据集,完成风险评级分类。通过数据实验的结果可以发现:与经典的机器学习方法相比,文中提出的基于群体决策的三支分类方法更加关注风险的规避,在各个数据集上的分类表现均有稳定且较优的结果,说明通过发现专家领域知识,利用数据的客观信息辅助专家评估风险有助于解决不同背景的决策问题。

基于多准则决策的替格瑞洛联合替罗非班治疗急性冠脉综合征的风险-效益评价

目的基于多准则决策(MCDM)模型评价替格瑞洛联合替罗非班治疗急性冠脉综合征(ACS)的风险与效益。方法选取2019年12月~2022年2月于秦皇岛市第一医院就诊的ACS患者(n=136)为研究对象;根据随机数字表法,分为A组(n=68,替格瑞洛+替罗非班)和B组(n=68,替格瑞洛)。建立治疗ACS的MCDM模型。结果治疗后,与B组相比,A组患者的左室射血分数(LVEF)、活化部分凝血活酶时间(APTT)以及总有效率更大(均P<0.01),左室收缩末内径(LVESd)、左室舒张末内径(LVEDd)、D-二聚体(D-D)、纤维蛋白原(FIB)、基质金属蛋白酶-9(MMP-9)、髓过氧化物酶(MPO)、主要不良心血管事件(MACE)(均P<0.01)以及不良反应(ADR)发生率(P<0.05)更小。Meta分析结果发现,与B组相比,A组疗效更显著,对改善心功能、凝血功能以及炎性反应更有优势,MACE以及ADR发生概率显著降低。计算结果显示,A组效益高且风险低,效益-风险总值为65,B组为53,且A组100%优于B组。结论对于ACS患者的治疗,替格瑞洛联合替罗非班效果较好,可显著改善凝血以及心功能,减轻炎性反应,并降低MACE以及ADR发生概率。

典型区域火灾风险数据的特征挖掘研究

随物联网与大数据的技术发展,我国城市火灾风险防治工作日益智能化。城市社会治理和日常消防工作中积累了大量多维度、动态的数据,为更有价值的数据挖掘提供了基础。故对政府公开的基础数据和消防部门业务平台的专业数据,采用数据挖掘方法进行深入分析研究。首先,描述性分析数据的统计分布特征;其次,采用主成分分析、决策树信息增益算法,研究火灾风险与环境因素数据的关系特征,构建降维分析模型;最后,深化分析模型输出的数据规律,研究数据集各属性间变化的特征趋势,为消防大数据建设和应用提出建议。

基于决策树算法的胃癌患者腹腔镜术后发生肺动脉栓塞的风险预测模型的建立

目的:对胃癌患者在腹腔镜手术后发生肺动脉栓塞(PE)的影响因素进行分析,并建立决策树模型。方法:回顾性收集我院于2018年1月—2022年6月行腹腔镜手术的胃癌患者118例为研究对象,依据胃癌患者在腹腔镜手术后是否发生肺动脉栓塞,分为肺动脉栓塞组与非肺动脉栓塞组,分析胃癌患者腹腔镜术后发生肺动脉栓塞的危险因素,采用SPSS Modeler软件构建胃癌患者腹腔镜术后发生肺动脉栓塞的决策树模型,并分析其预测效能。结果:单因素分析结果显示,年龄、围术期是否输注红细胞、下肢DVT、手术时间、术后第1天D-二聚体水平等资料皆存在统计学差异(P<0.05);多因素Logistic回归分析结果显示,年龄>60岁、围术期输注红细胞、下肢深静脉血栓形成(DVT)、手术时间≥3h、术后第1天D-二聚体水平是胃癌患者腹腔镜术后发生肺动脉栓塞的危险因素;构建了胃癌患者腹腔镜术后发生肺动脉栓塞的决策树模型,决策树模型共5层,13个节点,模型选择了年龄>60岁、围术期输注红细胞、下肢DVT、手术时间≥3h、术后第1天D-二聚体水平5个临床特征作为模型的节点,其中重要性排名第一的预测因子是术后第1天D-二聚体水平。胃癌患者腹腔镜术后发生肺动脉栓塞的决策树模型AUC是0.859(95%CI:0.783~0.917),胃癌患者腹腔镜术后发生肺动脉栓塞的Logistic回归模型的AUC是0.763(95%CI:0.676~0.836),决策树模型与Logistic回归模型的delong检验结果为Z=2.350,P=0.019。结论:年龄>60岁、围术期输注红细胞、下肢DVT、手术时间≥3h、术后第1天D-二聚体水平是胃癌患者腹腔镜术后发生肺动脉栓塞的危险因素。本研究构建的胃癌患者腹腔镜术后发生肺动脉栓塞的决策树模型预测效能较为优异,有利于早期精准鉴别胃癌患者腹腔镜术后PE的发生。

大数据分析在高速公路智慧运营决策中的价值与影响

高速公路对社会的进步有着重要的作用,智慧运营是提升交通运行效率,确保道路行驶安全的关键因素。作为一种专业的信息处理方法,大数据分析具备出色的能力,在高速公路智能化运营决策领域中具有的突出的地位与深远的作用。文中重点研究了大数据分析在高速公路智能化运营场景中的实践与应用,审视了其在决策过程中扮演的角色及其重要性。

Risk Acceptability and Cost-Effectiveness of Protective Measures Against Terrorist Threats to Built Infrastructure Considering Multiple Threat Scenarios

Decisions are often needed about the need and/or extent of protective measures against explosive blast loads on built infrastructure. A decision support analysis considers fatality risks and cost-effectiveness of protective measures expressed in terms of expected cost spent on risk reduction per life saved for terrorist threats to infrastructure. The analysis is applicable to any item of infrastructure, but in this paper is applied to casualties arising from building facade glazing damage. Risks may be compared with risk acceptance criteria in the form of quantitative safety goals. The risk acceptability and cost-effectiveness of protective measures includes cost of the protective measures, attack probability,reduction in risk due to protective measures,probability of fatality conditional on successful terrorist attack and number of exposed individuals.

Benefit-Risk Assessment for PD-1/PD-L1 Inhibitors in the Treatment of Non-Small Cell Lung Cancer

Objective To explore the benefits and risks of PD-1/PD-L1 inhibitors Atezolizumab and Nivolumab in the treatment of non-squamous non-small cell lung cancer and provide some references for clinicians.Methods Based on the data results of relevant studies published by ClinicalTrical.gov in the US clinical trial database and foreign peer-reviewed journals,the internationally recognized multi-criteria decision analysis(MCDA)model was used to assess the benefit and risk of PD-1/PD-L1 inhibitors for non-squamous non-small lung cancer comprehensively.Finally,a sensitivity analysis was performed to test the sensitivity of the weight to the evaluation.Results and Conclusion The benefit-risk evaluation result of Atezolizumab for the treatment of non-squamous non-small cell lung cancer is better than that of Nivolumab.Specifically,Atezolizumab has more benefits than Nivolumab with a lower risk.The results of MCDA model in drug benefit and risk evaluation are easy to understand.However,the selection of indicators in the model and the degree of data acquisition are limited.The evaluation results of the MCDA model should be comprehensively viewed with other evaluations to make decisions objectively.

中小水电站水库汛期运行调度多目标风险分析

针对中小水电站水库在汛期调度运行过程中常常因为调节库容小、调洪决策时间短、机组最大水头和上游库区淹没限制等特点,而导致其汛期无论洪水量级大小常以较低水位运行造成洪水资源化效益得不到充分发挥的问题,重点考虑预报入库洪峰流量和预报误差不确定性的影响,以发电效益最大和防洪风险最小为目标,建立了中小水电站水库汛期运行调度多目标风险分析模型,并给出了当预报入库洪峰流量在不同范围时的汛期最优水位的求解方法。对龟都府水电站水库的验证结果表明,当水库面临不同量级的洪水时,通过效益和风险的协调可得到最优的运行水位,达到小洪水时增加发电效益和大洪水时减小洪灾损失的目的,为变化环境下中小水电站水库汛期运行调度提供了参考。

多准则决策分析在药品管理领域中的应用研究进展

多准则决策分析(MCDA)是一种系统的决策方法和思维,是运筹学的一个分支学科,其应用范围非常广泛。近几年,MCDA在药品评估、遴选和定价等药品管理领域的应用迅速增加。本文通过检索相关文献,对MCDA的方法学及其在国内外药品管理领域的应用进行综述,以期为药品管理领域的决策行为提供参考依据。

食管异物术后食管穿孔预测模型建立与验证

目的构建食管异物术后食管穿孔的预测模型,预测食管异物术后食管穿孔的发生几率。方法回顾性收集天门市第一人民医院耳鼻咽喉头颈外科2012年1月~2022年3月1137例食管异物患者的病例资料,按照入院时间顺序分为建模组(810例)和验证组(327例),所有患者均行食管镜食管异物探查术,根据术中食管有无穿孔,分为无食管穿孔组和食管穿孔组。对建模组进行lasso回归筛选变量以及通过随机森林对自变量重要性进行排序,纳入不同自变量构建模型1和模型2,两个模型在区分度、校准度、临床适用度三个方面进行对比,并且进行赤池信息准则比较,内部验证采用Bootstrap法10重交叉验证1000次进行验证,模型区分度采用受试者工作特征曲线评估Logistic回归模型预测价值,采用Hosmer-Lemeshow来评价模型校准度,临床适用度采用绘制临床决策曲线,最后绘制nomogram图展示预测结果。结果1137例食管异物患者均顺利取出异物,248例出现食管穿孔,食管穿孔的发生率约为21.8%(248/1137)。模型1在区分度、校准都及临床适用度三个方面较模型2优势,并且赤池信息准则较小,最终模型1为本次研究的预测模型。建模组Logistic回归显示居住地区、年龄、民族、嵌顿时间、手术时间是食管异物术后食管穿孔的独立危险因素。建模组中预测概率ROC曲线下面积为0.71(95%CI:0.664~0.756),验证组预测概率ROC曲线下面积为0.703(95%CI:0.634~0.771);当约登指数最大时,约登指数为0.4,此时灵敏度=0.82,特异度=0.58,曲线下面积为0.7,此时对应的P=0.208,根据P=1/(1+e-y),可计算出此时Y=-1.34,对建模组进行内部验证,采用Bootstrap法10重交叉验证1000次进行内部验证,准确性为0.778,kappa一致性为0.126,AUC为0.699;建模组模型1中Hosmer-Lemeshow拟合优度检测显示χ^(2)=0.004,P=1,验证组Hosmer-Lemeshow显示χ^(2)=9.13,P=0.10,表明模型具有良好的辨别能力,最后展示临床决策曲线及列线图。结论本回归模型预测准确度较好,可为临床医务人员术前预测食管异物术后可能发生食管穿孔提供参考。

基于可拓云模型的建设工程质量检测机构运行风险评价研究

为准确识别和评价建设工程质量检测机构运行风险,从检测质量和检测工作合规性两个维度构建建设工程质量检测机构运行风险评价指标体系;采用群决策层次分析法获得综合指标权重,融合物元可拓理论和云模型,建立建设工程质量检测机构运行风险评价模型,并对某建设工程质量检测机构进行了评价模型案例应用,验证了模型的适用性和实用性。研究成果对于量化评价建设工程质量检测机构运行风险,维护建设工程质量检测行业秩序具有重要参考价值。