K-means algorithm is one of the most widely used algorithms in the clustering analysis. To deal with the problem caused by the random selection of initial center points in the traditional al- gorithm, this paper propo...K-means algorithm is one of the most widely used algorithms in the clustering analysis. To deal with the problem caused by the random selection of initial center points in the traditional al- gorithm, this paper proposes an improved K-means algorithm based on the similarity matrix. The im- proved algorithm can effectively avoid the random selection of initial center points, therefore it can provide effective initial points for clustering process, and reduce the fluctuation of clustering results which are resulted from initial points selections, thus a better clustering quality can be obtained. The experimental results also show that the F-measure of the improved K-means algorithm has been greatly improved and the clustering results are more stable.展开更多
The status and the variation of electrical resistance of impacted carbon fiber/epoxy-matrix composites were studied by ultrasonic F-scan and electrical resistance measurement The experimental results shows that impact...The status and the variation of electrical resistance of impacted carbon fiber/epoxy-matrix composites were studied by ultrasonic F-scan and electrical resistance measurement The experimental results shows that impact damage energy threshold value of carbon fabric/epoxy-matrix composites can determine by using ultrasonic F-scan. When the impact energy exceeds the threshold value, damage is generated in composites. Electrical resistance of impacted composites is changed owing to the contact of each carbon fiber unit in composites, which cause a change of the series-parallel in conductors. The veracity of detecting impact damage in composites can be improved in this case.展开更多
设T=A 0 U B是形式三角矩阵环,其中A,B是环,U是(B,A)-双模.利用Hom函子和伴随同构等理论,刻画形式三角矩阵环T上的F-Gorenstein平坦模结构,并证明若BU的平坦维数有限,U A的平坦维数有限且对任意的余挠左A-模C,有U■AC是余挠左B-模,则左T...设T=A 0 U B是形式三角矩阵环,其中A,B是环,U是(B,A)-双模.利用Hom函子和伴随同构等理论,刻画形式三角矩阵环T上的F-Gorenstein平坦模结构,并证明若BU的平坦维数有限,U A的平坦维数有限且对任意的余挠左A-模C,有U■AC是余挠左B-模,则左T-模M_(1)/M_(2)φ^(M)是F-Gorenstein平坦模当且仅当M_(1)是F-Gorenstein平坦左A-模,Cokerφ^(M)是F-Gorenstein平坦左B-模,且φ^(M):U■AM 1→M_(2)是单射.展开更多
In this paper we deal with the characteristic polynomial of finite Riodan matix. We giveseveral forms of its explicit expressions. Its applications to combinatorial identities, specially to F-Lidentities, are stated.
Riodan Matrix is a lower triangular matrix of infinite order with certainly restricted conditions. In this paper, the author defines two kinds of finite Riodan matrices which are not limited to lower triangular. Prope...Riodan Matrix is a lower triangular matrix of infinite order with certainly restricted conditions. In this paper, the author defines two kinds of finite Riodan matrices which are not limited to lower triangular. Properties of group theory of the two kinds matrices are considered. Applications of the finite Riodan matrices are researched.展开更多
轨道交通网络中乘客的出行受网络结构和运营状况变化的影响,个体出行偏好对这些变化的响应也各异。为分析轨道交通远郊区段计划性停运对常乘客的出行转移影响,本文提出考虑转移类型和转移比例的乘客出行特征刻画方法,结合时段属性生成...轨道交通网络中乘客的出行受网络结构和运营状况变化的影响,个体出行偏好对这些变化的响应也各异。为分析轨道交通远郊区段计划性停运对常乘客的出行转移影响,本文提出考虑转移类型和转移比例的乘客出行特征刻画方法,结合时段属性生成乘客特征—时序(FeatureTemporal,F-T)矩阵;通过改进的欧氏距离计算F-T矩阵间的相似性,实现F-T矩阵的相似性度量;提出一种基于相似度矩阵的K-Means聚类和层次聚类相结合的两步聚类方法(Two-step Clustering of K-Means Clustering and Hierarchical Clustering,KMHC)划分乘客影响群体,分析影响乘客出行转移的因素;以新冠肺炎疫情期间上海轨道交通11号线昆山段停运作为实例,对本文方法进行验证。研究结果表明:昆山段停运后,常乘客呈现出5种主要的出行转移影响群体,占常乘客总数的94.4%;各影响群体的转移距离、通勤时间和出行频率差异明显,是影响区段停运后常乘客出行选择的重要因素。本文方法可为其他计划性停运场景提供借鉴和参考,也可为区段停运后的网络客流变化预测,行车和客运组织方案优化提供支撑。展开更多
文摘K-means algorithm is one of the most widely used algorithms in the clustering analysis. To deal with the problem caused by the random selection of initial center points in the traditional al- gorithm, this paper proposes an improved K-means algorithm based on the similarity matrix. The im- proved algorithm can effectively avoid the random selection of initial center points, therefore it can provide effective initial points for clustering process, and reduce the fluctuation of clustering results which are resulted from initial points selections, thus a better clustering quality can be obtained. The experimental results also show that the F-measure of the improved K-means algorithm has been greatly improved and the clustering results are more stable.
基金Funded by the Key Laboratory of Nondestructive Testing (Nanchang Hangkong University), Ministry of Education, China(No.ZD200829001)
文摘The status and the variation of electrical resistance of impacted carbon fiber/epoxy-matrix composites were studied by ultrasonic F-scan and electrical resistance measurement The experimental results shows that impact damage energy threshold value of carbon fabric/epoxy-matrix composites can determine by using ultrasonic F-scan. When the impact energy exceeds the threshold value, damage is generated in composites. Electrical resistance of impacted composites is changed owing to the contact of each carbon fiber unit in composites, which cause a change of the series-parallel in conductors. The veracity of detecting impact damage in composites can be improved in this case.
文摘In this paper we deal with the characteristic polynomial of finite Riodan matix. We giveseveral forms of its explicit expressions. Its applications to combinatorial identities, specially to F-Lidentities, are stated.
文摘Riodan Matrix is a lower triangular matrix of infinite order with certainly restricted conditions. In this paper, the author defines two kinds of finite Riodan matrices which are not limited to lower triangular. Properties of group theory of the two kinds matrices are considered. Applications of the finite Riodan matrices are researched.
文摘轨道交通网络中乘客的出行受网络结构和运营状况变化的影响,个体出行偏好对这些变化的响应也各异。为分析轨道交通远郊区段计划性停运对常乘客的出行转移影响,本文提出考虑转移类型和转移比例的乘客出行特征刻画方法,结合时段属性生成乘客特征—时序(FeatureTemporal,F-T)矩阵;通过改进的欧氏距离计算F-T矩阵间的相似性,实现F-T矩阵的相似性度量;提出一种基于相似度矩阵的K-Means聚类和层次聚类相结合的两步聚类方法(Two-step Clustering of K-Means Clustering and Hierarchical Clustering,KMHC)划分乘客影响群体,分析影响乘客出行转移的因素;以新冠肺炎疫情期间上海轨道交通11号线昆山段停运作为实例,对本文方法进行验证。研究结果表明:昆山段停运后,常乘客呈现出5种主要的出行转移影响群体,占常乘客总数的94.4%;各影响群体的转移距离、通勤时间和出行频率差异明显,是影响区段停运后常乘客出行选择的重要因素。本文方法可为其他计划性停运场景提供借鉴和参考,也可为区段停运后的网络客流变化预测,行车和客运组织方案优化提供支撑。
