针对传统故障模式和影响分析(failure mode and effect analysis,FMEA)方法存在评价使用精确数量化造成专家风险评估信息的丢失、忽略风险指标之间的相对重要性以及由于专家有限理性导致的评价固有的随机性等问题,利用区间值直觉模糊集...针对传统故障模式和影响分析(failure mode and effect analysis,FMEA)方法存在评价使用精确数量化造成专家风险评估信息的丢失、忽略风险指标之间的相对重要性以及由于专家有限理性导致的评价固有的随机性等问题,利用区间值直觉模糊集和云模型构建了一种改进的FMEA风险评估方法。首先,引入区间值直觉模糊集(IVIFS)来描述专家评价信息的复杂性和不确定性,通过运用区间值直觉模糊熵,计算专家权重和风险因子的权重;其次,采用云模型的方法,通过比较各支持云模型和反对云模型与正、负理想云模型的正、负相似度,获得故障模式评价值的综合相似度,通过对综合相似度大小排序得到各故障模式风险排序;最后,以自动扶梯的梯级、踏板和胶带风险评估为例进行分析,验证该评估方法的实用性和可行性。展开更多
Intuitionistic fuzzy sets(IFSs) are useful means to describe and deal with vague and uncertain data.An intuitionistic fuzzy C-means algorithm to cluster IFSs is developed.In each stage of the intuitionistic fuzzy C-me...Intuitionistic fuzzy sets(IFSs) are useful means to describe and deal with vague and uncertain data.An intuitionistic fuzzy C-means algorithm to cluster IFSs is developed.In each stage of the intuitionistic fuzzy C-means method the seeds are modified,and for each IFS a membership degree to each of the clusters is estimated.In the end of the algorithm,all the given IFSs are clustered according to the estimated membership degrees.Furthermore,the algorithm is extended for clustering interval-valued intuitionistic fuzzy sets(IVIFSs).Finally,the developed algorithms are illustrated through conducting experiments on both the real-world and simulated data sets.展开更多
The intuitionistic fuzzy set(IFS) based on fuzzy theory,which is of high efficiency to solve the fuzzy problem, has been introduced by Atanassov. Subsequently, he pushed the research one step further from the IFS to t...The intuitionistic fuzzy set(IFS) based on fuzzy theory,which is of high efficiency to solve the fuzzy problem, has been introduced by Atanassov. Subsequently, he pushed the research one step further from the IFS to the interval valued intuitionistic fuzzy set(IVIFS). On the basis of fuzzy set(FS), the IFS is a generalization concept. And the IFS is generalized to the IVIFS.In this paper, the definition of the sixth Cartesian product over IVIFSs is first introduced and its some properties are explored.We prove some equalities based on the operation and the relation over IVIFSs. Finally, we present one geometric interpretation and a numerical example of the sixth Cartesian product over IVIFSs.展开更多
The paper aims at the problem of multi-targets threat degree being hard to be evaluated accurately in complex air defense battlefield environments. Combined with multi-sensors information fusion and interval-valued in...The paper aims at the problem of multi-targets threat degree being hard to be evaluated accurately in complex air defense battlefield environments. Combined with multi-sensors information fusion and interval-valued intuitionistic fuzzy sets(IVIFS) theories, the target priority determination is studied. The score and accuracy functions of IVIFS are improved with thinking about the hesitating information in order to increase the rationality.Then, the influence factors of target priority and the nonlinear relationship between the influence factors and target priority are analyzed. Next, the algorithms for calculating the factor weights and sensor weights are given. Based on the theory of IVIFS and technique for order preference by similarity to an ideal solution(TOPSIS), two methods of target priority determination based on the IVIFS and TOPSIS are proposed. At last, an application example verifies the effectiveness and flexibility of the proposed algorithms.展开更多
文摘针对传统故障模式和影响分析(failure mode and effect analysis,FMEA)方法存在评价使用精确数量化造成专家风险评估信息的丢失、忽略风险指标之间的相对重要性以及由于专家有限理性导致的评价固有的随机性等问题,利用区间值直觉模糊集和云模型构建了一种改进的FMEA风险评估方法。首先,引入区间值直觉模糊集(IVIFS)来描述专家评价信息的复杂性和不确定性,通过运用区间值直觉模糊熵,计算专家权重和风险因子的权重;其次,采用云模型的方法,通过比较各支持云模型和反对云模型与正、负理想云模型的正、负相似度,获得故障模式评价值的综合相似度,通过对综合相似度大小排序得到各故障模式风险排序;最后,以自动扶梯的梯级、踏板和胶带风险评估为例进行分析,验证该评估方法的实用性和可行性。
基金National Natural Science Foundation of China(60474023)Science and Technology Key Project Fund of Ministry of Education(03184)The Major State Basic Research Development Program of China(2002CB312200)
基金supported by the National Natural Science Foundation of China for Distinguished Young Scholars(70625005)
文摘Intuitionistic fuzzy sets(IFSs) are useful means to describe and deal with vague and uncertain data.An intuitionistic fuzzy C-means algorithm to cluster IFSs is developed.In each stage of the intuitionistic fuzzy C-means method the seeds are modified,and for each IFS a membership degree to each of the clusters is estimated.In the end of the algorithm,all the given IFSs are clustered according to the estimated membership degrees.Furthermore,the algorithm is extended for clustering interval-valued intuitionistic fuzzy sets(IVIFSs).Finally,the developed algorithms are illustrated through conducting experiments on both the real-world and simulated data sets.
基金supported by the National Natural Science Foundation of China(61373174)
文摘The intuitionistic fuzzy set(IFS) based on fuzzy theory,which is of high efficiency to solve the fuzzy problem, has been introduced by Atanassov. Subsequently, he pushed the research one step further from the IFS to the interval valued intuitionistic fuzzy set(IVIFS). On the basis of fuzzy set(FS), the IFS is a generalization concept. And the IFS is generalized to the IVIFS.In this paper, the definition of the sixth Cartesian product over IVIFSs is first introduced and its some properties are explored.We prove some equalities based on the operation and the relation over IVIFSs. Finally, we present one geometric interpretation and a numerical example of the sixth Cartesian product over IVIFSs.
基金the National Defense Pre-Research Foundation of China(No.9140A27020211JB34)
文摘The paper aims at the problem of multi-targets threat degree being hard to be evaluated accurately in complex air defense battlefield environments. Combined with multi-sensors information fusion and interval-valued intuitionistic fuzzy sets(IVIFS) theories, the target priority determination is studied. The score and accuracy functions of IVIFS are improved with thinking about the hesitating information in order to increase the rationality.Then, the influence factors of target priority and the nonlinear relationship between the influence factors and target priority are analyzed. Next, the algorithms for calculating the factor weights and sensor weights are given. Based on the theory of IVIFS and technique for order preference by similarity to an ideal solution(TOPSIS), two methods of target priority determination based on the IVIFS and TOPSIS are proposed. At last, an application example verifies the effectiveness and flexibility of the proposed algorithms.
