partitioningAn efficient partitioning algorithm for mixed-mode placement, extended-MFFC-based partitioning, is presented. It combines the bottom-up clustering and the top-down partitioning together. To do this, designers can not only cluster cells considering logic dependency but also partition them ...
Evaluation results show that it provides adequate subsystems for parallel restoration. Unlike some existing partitioning strategies, the proposed strategy can be used to partition a power system into multiple subsystems in a single execution. 展开 ...
the theory of fragmentation has a long history (see for example [1]) and several procedures have been analyzed for splitting tabular data into fragments and subsequently assigning fragments to servers. Other database systems with key-based access (like key-value stores...
Partitioning methods (K-means, PAM clustering) and hierarchical clustering are suitable for finding spherical-shaped clusters or convex clusters. In other words, they work well only for compact and well separated clusters. Moreover, they are also severely affected by the presence of noise and outli...
K-means [2] is a partition-based clustering algorithm, targeting the partitioning of instances into k clusters, based on their similarity, leveraging an iterative procedure that assigns instances to the nearest cluster centroid. K-modes [3,4], a variation of k-means, is suitable for categorical...
We explore the capabilities of today's high-end Graphics processing units (GPU) on desktop computers toefficientlyperform hierarchical agglomerative clustering (HAC) through partitioning of gene expressions.Our focus is to significantly reduce time and memory bottlenecks of the traditional HAC algorithm ...
[1]) and several procedures have been analyzed for splitting tabular data into fragments and subsequently assigning fragments to servers. Other database systems with key-based access (like key-value stores, document databases, or column family stores) use range-based partitioning or consistent ...
DSGA: a distributed segment-based genetic algorithm for multi-objective outsourced database partitioning. Inf Sci. 2022;612:864–86. Article Google Scholar Singh A, Khehra BS, Mavi BS. Simplified-BBO for non-redundant allocation of data in distributed database design. In: 2021 IEEE ...
For instance, as a partitioning-based clustering method, Kmeans [7] has its distinctive characteristics of being simple, efficient and user-friendly. Nevertheless, Kmeans suffers from the initialization problem, requires users to pre-define the cluster number, and is only good at detecting spherical...
In order to overcome these restrictions, a consensus clustering algorithm based on partitioning similarity graph is proposed here. In short, the contributions of the present paper are as follow: The rest of the paper is organized as follow: Section 2 formulates the consensus clustering problem. ...