In this paper, a necessary condition for a bipartite graph λK m,n to be K 1,k factorizable and a sufficient condition for kK m,n to have a K 1,k factorization whenever k is a prime numbe...In this paper, a necessary condition for a bipartite graph λK m,n to be K 1,k factorizable and a sufficient condition for kK m,n to have a K 1,k factorization whenever k is a prime number are given.展开更多
Data is humongous today because of the extensive use of World WideWeb, Social Media and Intelligent Systems. This data can be very important anduseful if it is harnessed carefully and correctly. Useful information can...Data is humongous today because of the extensive use of World WideWeb, Social Media and Intelligent Systems. This data can be very important anduseful if it is harnessed carefully and correctly. Useful information can beextracted from this massive data using the Data Mining process. The informationextracted can be used to make vital decisions in various industries. Clustering is avery popular Data Mining method which divides the data points into differentgroups such that all similar data points form a part of the same group. Clusteringmethods are of various types. Many parameters and indexes exist for the evaluationand comparison of these methods. In this paper, we have compared partitioningbased methods K-Means, Fuzzy C-Means (FCM), Partitioning AroundMedoids (PAM) and Clustering Large Application (CLARA) on secure perturbeddata. Comparison and identification has been done for the method which performsbetter for analyzing the data perturbed using Extended NMF on the basis of thevalues of various indexes like Dunn Index, Silhouette Index, Xie-Beni Indexand Davies-Bouldin Index.展开更多
The purpose of the present paper is to show a new numeric and symbolic algorithm for inverting a general nonsingular k-heptadiagonal matrix.This work is based on Doolitle LU factorization of the matrix.We obtain a ser...The purpose of the present paper is to show a new numeric and symbolic algorithm for inverting a general nonsingular k-heptadiagonal matrix.This work is based on Doolitle LU factorization of the matrix.We obtain a series of recursive relationships then we use them for constructing a novel algorithm for inverting a k-heptadiagonal matrix.The computational cost of the algorithm is calculated.Some illustrative examples are given to demonstrate the effectiveness of the proposed method.展开更多
为了解决源数据维数较大的问题,提出了一种基于非负矩阵分解(NMF)的同调机群识别方法。采用发电机角速度作为源数据,使用NMF算法对其进行降维。由于此低维矩阵具有非负性质,因而该模型在消除冗余数据、降低维数的同时,保留了原始问题的...为了解决源数据维数较大的问题,提出了一种基于非负矩阵分解(NMF)的同调机群识别方法。采用发电机角速度作为源数据,使用NMF算法对其进行降维。由于此低维矩阵具有非负性质,因而该模型在消除冗余数据、降低维数的同时,保留了原始问题的实际意义。对低维矩阵归一化,再利用K均值聚类算法对其进行聚类,达到同调机群的分群目的。通过New England 10机39节点系统比较了基于NMF和主成分分析方法的分群效果,验证了基于NMF的同调机群识别方法的有效性。展开更多
文摘In this paper, a necessary condition for a bipartite graph λK m,n to be K 1,k factorizable and a sufficient condition for kK m,n to have a K 1,k factorization whenever k is a prime number are given.
文摘Data is humongous today because of the extensive use of World WideWeb, Social Media and Intelligent Systems. This data can be very important anduseful if it is harnessed carefully and correctly. Useful information can beextracted from this massive data using the Data Mining process. The informationextracted can be used to make vital decisions in various industries. Clustering is avery popular Data Mining method which divides the data points into differentgroups such that all similar data points form a part of the same group. Clusteringmethods are of various types. Many parameters and indexes exist for the evaluationand comparison of these methods. In this paper, we have compared partitioningbased methods K-Means, Fuzzy C-Means (FCM), Partitioning AroundMedoids (PAM) and Clustering Large Application (CLARA) on secure perturbeddata. Comparison and identification has been done for the method which performsbetter for analyzing the data perturbed using Extended NMF on the basis of thevalues of various indexes like Dunn Index, Silhouette Index, Xie-Beni Indexand Davies-Bouldin Index.
文摘The purpose of the present paper is to show a new numeric and symbolic algorithm for inverting a general nonsingular k-heptadiagonal matrix.This work is based on Doolitle LU factorization of the matrix.We obtain a series of recursive relationships then we use them for constructing a novel algorithm for inverting a k-heptadiagonal matrix.The computational cost of the algorithm is calculated.Some illustrative examples are given to demonstrate the effectiveness of the proposed method.
文摘为了解决源数据维数较大的问题,提出了一种基于非负矩阵分解(NMF)的同调机群识别方法。采用发电机角速度作为源数据,使用NMF算法对其进行降维。由于此低维矩阵具有非负性质,因而该模型在消除冗余数据、降低维数的同时,保留了原始问题的实际意义。对低维矩阵归一化,再利用K均值聚类算法对其进行聚类,达到同调机群的分群目的。通过New England 10机39节点系统比较了基于NMF和主成分分析方法的分群效果,验证了基于NMF的同调机群识别方法的有效性。
