The contribution rate of equipment system-of-systems architecture(ESoSA)is an important index to evaluate the equipment update,development,and architecture optimization.Since the traditional ESoSA contribution rate ev...The contribution rate of equipment system-of-systems architecture(ESoSA)is an important index to evaluate the equipment update,development,and architecture optimization.Since the traditional ESoSA contribution rate evaluation method does not make full use of the fuzzy information and uncertain information in the equipment system-of-systems(ESoS),and the Bayesian network is an effective tool to solve the uncertain information,a new ESoSA contribution rate evaluation method based on the fuzzy Bayesian network(FBN)is proposed.Firstly,based on the operation loop theory,an ESoSA is constructed considering three aspects:reconnaissance equipment,decision equipment,and strike equipment.Next,the fuzzy set theory is introduced to construct the FBN of ESoSA to deal with fuzzy information and uncertain information.Furthermore,the fuzzy importance index of the root node of the FBN is used to calculate the contribution rate of the ESoSA,and the ESoSA contribution rate evaluation model based on the root node fuzzy importance is established.Finally,the feasibility and rationality of this method are validated via an empirical case study of aviation ESoSA.Compared with traditional methods,the evaluation method based on FBN takes various failure states of equipment into consideration,is free of acquiring accurate probability of traditional equipment failure,and models the uncertainty of the relationship between equipment.The proposed method not only supplements and improves the ESoSA contribution rate assessment method,but also broadens the application scope of the Bayesian network.展开更多
合理应用机械设计知识可以辅助提升创新设计的效率和质量。本文立足于云模式下的机械设计过程,提出基于行为-结构-知识的机械设计知识解构模型;提出一种云制造模式下基于RoughANP的机械设计知识优选推送策略,该方法充分结合了粗糙集理论...合理应用机械设计知识可以辅助提升创新设计的效率和质量。本文立足于云模式下的机械设计过程,提出基于行为-结构-知识的机械设计知识解构模型;提出一种云制造模式下基于RoughANP的机械设计知识优选推送策略,该方法充分结合了粗糙集理论(Rough set theory)在处理模糊性和不确定性方面的优势以及网络层次分析法(ANP)在处理多目标评估问题的优势。最后以电动铲运机设计为案例,验证了该机械设计知识优选推送策略的有效性。展开更多
为有效评估和降低海上平台穿刺风险,提出一种基于事故树分析(fault tree analysis,FTA)和贝叶斯网络(Bayesian network,BN)的混合风险识别模型。根据相关事故报告和现有文献,构建海上平台穿刺事故的事故树模型。结合模糊集理论和事故树...为有效评估和降低海上平台穿刺风险,提出一种基于事故树分析(fault tree analysis,FTA)和贝叶斯网络(Bayesian network,BN)的混合风险识别模型。根据相关事故报告和现有文献,构建海上平台穿刺事故的事故树模型。结合模糊集理论和事故树模型计算基本事件的概率,并根据映射规则将事故树模型转换为BN模型。通过BN模型的诊断推理和敏感性分析识别海上平台穿刺事故的关键影响因素。结果表明:导致海上平台穿刺事故的关键影响因素为安全培训不足、人员应急经验不足、应急预案不完善、管理者决策失误以及穿刺发生突然且剧烈。该模型可以有效评估海上平台穿刺风险,并为制定有针对性的风险防控措施提供科学依据。展开更多
Rough set 理论已经在机器学习、从数据库中发现知识、决策支持和分析等方面得到了广泛应用。建立目标威胁模型,首先要挑选特征参数,这里采用知识约简方法选择目标的特征参数;利用神经网络理论建立了威胁模型,目标的威胁程度与特征参数...Rough set 理论已经在机器学习、从数据库中发现知识、决策支持和分析等方面得到了广泛应用。建立目标威胁模型,首先要挑选特征参数,这里采用知识约简方法选择目标的特征参数;利用神经网络理论建立了威胁模型,目标的威胁程度与特征参数的关系可通过神经网络的阀值和权值得到体现,实例表明该方法简单可行。展开更多
基金supported by the National Key Research and Development Project(2018YFB1700802)the National Natural Science Foundation of China(72071206)the Science and Technology Innovation Plan of Hunan Province(2020RC4046).
文摘The contribution rate of equipment system-of-systems architecture(ESoSA)is an important index to evaluate the equipment update,development,and architecture optimization.Since the traditional ESoSA contribution rate evaluation method does not make full use of the fuzzy information and uncertain information in the equipment system-of-systems(ESoS),and the Bayesian network is an effective tool to solve the uncertain information,a new ESoSA contribution rate evaluation method based on the fuzzy Bayesian network(FBN)is proposed.Firstly,based on the operation loop theory,an ESoSA is constructed considering three aspects:reconnaissance equipment,decision equipment,and strike equipment.Next,the fuzzy set theory is introduced to construct the FBN of ESoSA to deal with fuzzy information and uncertain information.Furthermore,the fuzzy importance index of the root node of the FBN is used to calculate the contribution rate of the ESoSA,and the ESoSA contribution rate evaluation model based on the root node fuzzy importance is established.Finally,the feasibility and rationality of this method are validated via an empirical case study of aviation ESoSA.Compared with traditional methods,the evaluation method based on FBN takes various failure states of equipment into consideration,is free of acquiring accurate probability of traditional equipment failure,and models the uncertainty of the relationship between equipment.The proposed method not only supplements and improves the ESoSA contribution rate assessment method,but also broadens the application scope of the Bayesian network.
文摘合理应用机械设计知识可以辅助提升创新设计的效率和质量。本文立足于云模式下的机械设计过程,提出基于行为-结构-知识的机械设计知识解构模型;提出一种云制造模式下基于RoughANP的机械设计知识优选推送策略,该方法充分结合了粗糙集理论(Rough set theory)在处理模糊性和不确定性方面的优势以及网络层次分析法(ANP)在处理多目标评估问题的优势。最后以电动铲运机设计为案例,验证了该机械设计知识优选推送策略的有效性。
文摘为有效评估和降低海上平台穿刺风险,提出一种基于事故树分析(fault tree analysis,FTA)和贝叶斯网络(Bayesian network,BN)的混合风险识别模型。根据相关事故报告和现有文献,构建海上平台穿刺事故的事故树模型。结合模糊集理论和事故树模型计算基本事件的概率,并根据映射规则将事故树模型转换为BN模型。通过BN模型的诊断推理和敏感性分析识别海上平台穿刺事故的关键影响因素。结果表明:导致海上平台穿刺事故的关键影响因素为安全培训不足、人员应急经验不足、应急预案不完善、管理者决策失误以及穿刺发生突然且剧烈。该模型可以有效评估海上平台穿刺风险,并为制定有针对性的风险防控措施提供科学依据。
