The analysis of changes in water quality in a monitoring network system is important because the sources of pollution vary in time and space. This study utilized analysis of the water quality index calculation, hierarchical cluster analysis, and mapping. This was achieved by assessing the water quality parameters of the samples collected from Galma River in Zaria, Northwestern Nigeria in wet an...

This paper presents a novel hierarchical clustering method using support vector machines. A common approach for hierarchical clustering is to use distance for the task. However, different choices for computing inter-cluster distances often lead to fairly distinct clustering outcomes, causing interpretation difficulties in practice. In this paper, we propose to use a one-class support vector mac...

We present a clustering algorithm for hierarchical traffic grooming in large WDM networks. In hierarchical grooming, the network is decomposed into clusters, and one hub node in each cluster is responsible for grooming traffic from and to the cluster. Hierarchical grooming scales to large network sizes and facilitates the control and management of traffic and network resources. Yet determining ...

In this work, a hierarchical ensemble of projected clustering algorithm for high-dimensional data is proposed. The basic concept of the algorithm is based on the active learning method (ALM) which is a fuzzy learning scheme, inspired by some behavioral features of human brain functionality. High-dimensional unsupervised active learning method (HUALM) is a clustering algorithm which blurs the da...

Energy is the main constraint in wireless sensor network. Hence to increase the lifetime of WSN, the requirement is to have an energy efficient routing protocol .For this purpose the hierarchical routing architecture is used wherein the whole network is divided into group of clusters and only cluster head is responsible for forwarding the data to base station directly. In hierarchical based arc...

To improve the Routing the Enhanced Routing protocol mechanism is used in Mobile ad hoc networks. The EHRP provides efficient and reliable routing paths. EHRP is compatible which reduces routing overhead and route discovery delay of the mobile ad hoc networks. The shortest hierarchical path is calculated based on the cluster head of different Clusters using the Cluster Table addressing scheme w...

Background: In clinical data subgroups can sometimes be identified using regression analysis of subgroup characteristics against some outcome variable, but in data samples without an available outcome variable cluster analysis is a suitable alternative. It is based on the concept that patients with closely related characteristics may also be more related in other fields like prognoses and treat...

Hierarchical clustering methods are widely used in various scientific domains such as molecular biology, medicine, economy, etc. Despite the maturity of the research field of hierarchical clustering, we have identified the following four goals which are not yet fully satisfied by previous methods: First, to guide the hierarchical clustering algorithm to identify only meaningful and valid cluste...

In this paper, we implement and compare three different clustering algorithms for the purpose of 3D image segmentation. Specifically, the K-means, Mean Shift, and Hierarchical methods are studied, and their performance is compared using cluster validity methods. Performance was analyzed in two ways, first by comparing independent results from each, and second, by comparing results where Hierarc...

We present a hierarchical maximum-margin clustering method for unsupervised data analysis. Our method extends beyond flat maximummargin clustering, and performs clustering recursively in a top-down manner. We propose an effective greedy splitting criteria for selecting which cluster to split next, and employ regularizers that enforce feature sharing/competition for capturing data semantics. Exp...