Grouping Multidimensional Data - Recent Advances in Clustering

Data Clustering: A User's Dilemma

Cluster analysis deals with the automatic discovery of the grouping of a set of patterns. Despite more than 40 years of research, there are still many challenges in data clustering from both theoretical and practical viewpoints. In this paper, we describe several recent advances in data clustering: clustering ensemble, feature selection, and clustering with constraints.

An Improved SSPCO Optimization Algorithm for Solve of the Clustering Problem

Swarm Intelligence (SI) is an innovative artificial intelligence technique for solving complex optimization problems. Data clustering is the process of grouping data into a number of clusters. The goal of data clustering is to make the data in the same cluster share a high degree of similarity while being very dissimilar to data from other clusters. Clustering algorithms have been applied to a ...

An Improved SSPCO Optimization Algorithm for Solve of the Clustering Problem

Swarm Intelligence (SI) is an innovative artificial intelligence technique for solving complex optimization problems. Data clustering is the process of grouping data into a number of clusters. The goal of data clustering is to make the data in the same cluster share a high degree of similarity while being very dissimilar to data from other clusters. Clustering algorithms have been applied to a ...

Clustering Very Large Data Sets with Principal Direction Divisive Partitioning

Hierarchal Grouping Strategy with Adaptive Power Tuning in ZigBee Wireless Sensor Networks

Designing wireless sensor networks should meet appropriate parameters such as quality of service (QoS) defined by different users. The variable physical conditions of the environment, processing and transmission power limitations and limited communication capabilities are the most important obstacles that influence QoS parameters such as throughput, delay, reliability and network lifetime. The ...