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基于复杂网络理论概算管理风险分析与控制研究
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作者 袁维 黄山 雍秀珍 《工程管理学报》 2023年第6期98-102,共5页
将复杂网络理论运用到概算管理风险分析,对建设项目全过程的4个阶段进行研究。通过分析文献和工程案例,识别出影响概算管理的风险因素并提取他们之间的相关关系,然后建立概算管理风险网络模型。利用节点度、网络直径及平均路径长度、聚... 将复杂网络理论运用到概算管理风险分析,对建设项目全过程的4个阶段进行研究。通过分析文献和工程案例,识别出影响概算管理的风险因素并提取他们之间的相关关系,然后建立概算管理风险网络模型。利用节点度、网络直径及平均路径长度、聚类系数、中介中心性等复杂网络指标对概算管理风险进行分析,识别出影响概算管理的关键风险因素。结果表明,设计变更、工期延误、施工索赔、施工成本增加是影响整个概算管理风险网络的主要因素;设计变更与概算编制不准确受到风险网络模型中多个因素的影响,具有较高的风险率。构建概算管理风险度评估模型,获得了不同边的风险度指标。针对风险度较大的边提出了断链措施,当风险传播时及时进行断链,可有效控制风险进一步传播,减少超概算事件的发生。 展开更多
关键词 概算管理 复杂网络理论 风险分析 风险网络模型 风险度评估
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基于SNA的PPP项目风险及扩散机制研究 被引量:1
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作者 宁若宇 刘伊生 《河南科学》 2020年第7期1148-1156,共9页
在对PPP项目风险因素进行系统识别和分析的基础上,以PPP项目常见风险因素为研究对象,通过网络化的视角建立了PPP项目风险因素关系网络模型.运用专家调查法和社会网络分析法更加系统地分析了PPP项目实施过程中可能面临的风险及各风险之... 在对PPP项目风险因素进行系统识别和分析的基础上,以PPP项目常见风险因素为研究对象,通过网络化的视角建立了PPP项目风险因素关系网络模型.运用专家调查法和社会网络分析法更加系统地分析了PPP项目实施过程中可能面临的风险及各风险之间关系、传播机制,寻找出了PPP项目中关键的风险因素,发现其风险因素连锁反应链及起到关键中介作用的桥节点.本研究为PPP项目风险分析提供了一种形象化、针对性的创新研究范式,同时有助于PPP项目实施过程中风险管控. 展开更多
关键词 PPP项目 社会网络分析 风险网络模型 扩散路径 风险管控
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基于SNA的PPP项目合同履约风险及扩散路径研究 被引量:4
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作者 吴秀宇 刘峰才 《工程管理学报》 2020年第5期97-102,共6页
为了缓解PPP项目合同履约困难的现象,从社会网络视角分析履约风险特征及关系。根据案例分析、专家打分等识别、量化风险,建立履约风险网络模型并通过社会网络分析的四类指标(整体网络结构特征、个体中心度、影响力及凝聚子群)来识别关... 为了缓解PPP项目合同履约困难的现象,从社会网络视角分析履约风险特征及关系。根据案例分析、专家打分等识别、量化风险,建立履约风险网络模型并通过社会网络分析的四类指标(整体网络结构特征、个体中心度、影响力及凝聚子群)来识别关键风险及潜在风险扩散路径。研究表明存在具有风险扩散路径的履约风险网络,其中,关键风险包括成本超支风险、工期逾期风险等;存在风险扩散路径,如工期逾期风险—政府干预风险—工程质量风险等;风险传播节点有运营费用过高风险等,从而为PPP项目合同的履约风险分析提供了新框架,有助于PPP项目履约过程中的风险管控。 展开更多
关键词 PPP项目合同履约 社会网络分析 履约风险网络模型 扩散路径 风险管控
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基于网络分析法的绿色企业可持续发展风险研究 被引量:2
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作者 李思捷 孟庆军 《经济研究导刊》 2018年第9期2-6,共5页
绿色企业的可持续发展是国家供给侧改革的重要部分,绿色企业的发展面临着投入资本较大、成本增加、资金回收困难等风险。这类企业需要在政府支持下重视管理工作,加强与金融和科研院所等其他组织合作等。运用优化的"钻石模型"... 绿色企业的可持续发展是国家供给侧改革的重要部分,绿色企业的发展面临着投入资本较大、成本增加、资金回收困难等风险。这类企业需要在政府支持下重视管理工作,加强与金融和科研院所等其他组织合作等。运用优化的"钻石模型"结合"网络分析法",有利于以定性和定量相结合的方法分析问题并提出对策。 展开更多
关键词 绿色企业 可持续发展 风险“双钻石模型”“网络分析法”
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Development of Bayesian Network Models for Risk-Based Ship Design 被引量:3
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作者 Dimitris Konovessis Wenkui Cai Dracos Vassalos 《Journal of Marine Science and Application》 2013年第2期140-151,共12页
In the past fifteen years, the attention of ship safety treatment as an objective rather than a constraint has started to sweep through the whole maritime industry. The risk-based ship design (RBD) methodology, advo... In the past fifteen years, the attention of ship safety treatment as an objective rather than a constraint has started to sweep through the whole maritime industry. The risk-based ship design (RBD) methodology, advocating systematic integration of risk assessment within the conventional design process has started to takeoff. Despite this wide recognition and increasing popularity, important factors that could potentially undermine the quality of the results come from both quantitative and qualitative aspects during the risk assessment process. This paper details a promising solution by developing a formalized methodology for risk assessment through effective storing and processing of historical data combined with data generated through first-principle approaches. This method should help to generate appropriate risk models in the selected platform (Bayesian networks) which can be employed for decision making at design stare. 展开更多
关键词 risk-based ship design risk assessment data mining Bayesian networks ship safety
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Risk-based water quality decision-making under small data using Bayesian network 被引量:3
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作者 张庆庆 许月萍 +1 位作者 田烨 张徐杰 《Journal of Central South University》 SCIE EI CAS 2012年第11期3215-3224,共10页
A knowledge-based network for Section Yidong Bridge,Dongyang River,one tributary of Qiantang River,Zhejiang Province,China,is established in order to model water quality in areas under small data.Then,based on normal ... A knowledge-based network for Section Yidong Bridge,Dongyang River,one tributary of Qiantang River,Zhejiang Province,China,is established in order to model water quality in areas under small data.Then,based on normal transformation of variables with routine monitoring data and normal assumption of variables without routine monitoring data,a conditional linear Gaussian Bayesian network is constructed.A "two-constraint selection" procedure is proposed to estimate potential parameter values under small data.Among all potential parameter values,the ones that are most probable are selected as the "representatives".Finally,the risks of pollutant concentration exceeding national water quality standards are calculated and pollution reduction decisions for decision-making reference are proposed.The final results show that conditional linear Gaussian Bayesian network and "two-constraint selection" procedure are very useful in evaluating risks when there is limited data and can help managers to make sound decisions under small data. 展开更多
关键词 water quality risk pollution reduction decisions Bayesian network conditional linear Gaussian Model small data
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SVM model for estimating the parameters of the probability-integral method of predicting mining subsidence 被引量:11
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作者 ZHANG Hua WANG Yun-jia LI Yong-feng 《Mining Science and Technology》 EI CAS 2009年第3期385-388,394,共5页
A new mathematical model to estimate the parameters of the probability-integral method for mining subsidence prediction is proposed.Based on least squares support vector machine(LS-SVM) theory, it is capable of improv... A new mathematical model to estimate the parameters of the probability-integral method for mining subsidence prediction is proposed.Based on least squares support vector machine(LS-SVM) theory, it is capable of improving the precision and reliability of mining subsidence prediction.Many of the geological and mining factors involved are related in a nonlinear way.The new model is based on statistical theory(SLT) and empirical risk minimization(ERM) principles.Typical data collected from observation stations were used for the learning and training samples.The calculated results from the LS-SVM model were compared with the prediction results of a back propagation neural network(BPNN) model.The results show that the parameters were more precisely predicted by the LS-SVM model than by the BPNN model.The LS-SVM model was faster in computation and had better generalized performance.It provides a highly effective method for calculating the predicting parameters of the probability-integral method. 展开更多
关键词 mining subsidence probability-integral method least squares support vector machine artificial neural networks
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Research on Risk Assessment of City Natural Disaster based on Neural Network
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作者 Xinyan WU 《International Journal of Technology Management》 2014年第7期109-111,共3页
Aiming at the selection of fuzzy AHP and fuzzy DH methods in the previous studies, this paper evaluate the qualitative index system using expert questionnaire, the self-learning BP neural network model to construct th... Aiming at the selection of fuzzy AHP and fuzzy DH methods in the previous studies, this paper evaluate the qualitative index system using expert questionnaire, the self-learning BP neural network model to construct the index of system, and complete the establishment of model, in order to avoid the serious subjectivity, and using statistical and measurement methods test the reliability index, analyze the validity of the evaluation index system and completeness. Finally, the paper validate the practicability of the model. 展开更多
关键词 Geological disaster disaster prevention and mitigation neural network risk assessment
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