Search Results - (( java implementation based algorithm ) OR ( using clusters clustering algorithm ))

Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

“…This project will use fuzzy k-means clustering algorithm to cluster the data because it is easy to implement and have many advantages. …”
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Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

“…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. …”
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A Toolkit for Simulation of Desktop Grid Environment by FOROUSHAN, PAYAM CHINI

“…A simulator for desktop grid environment has been developed using Java as the implementation language due to its wide popularity. …”
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Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform by Alias, Norma, Satam, Noriza, Abd. Ghaffar, Zarith Safiza, Darwis, Roziha, Hamzah, Norhafiza, Islam, Md. Rajibul

“…The development of this architecture is based on several programming language as it involves algorithm implementation on C, parallelization using Parallel Virtual Machine (PVM) and Java for web services development. …”
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A web-based implementation of k-means algorithms by Lee, Quan

“…Firstly, k-luster could incorporate additional clustering algorithms, or even classification algorithms in the future. …”
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Application-Programming Interface (API) for Song Recognition Systems by Murtadha Arif Sahbudin, Chakib Chaouch, Salvatore Serrano

“…An approach capable of recognizing an audio piece of music with an accuracy equal to 90% was further tested based on this result. In addition the implementation is done by algorithm using Java’s programming language, executed through an application developed in the Android operating system. …”

Clustering ensemble learning method based on incremental genetic algorithms by Ghaemi, Reza

“…Moreover, experiments demonstrate that final clustering solution generated by the proposed incremental genetic-based clustering ensemble algorithm using the pattern ensemble learning method possess comparative or better clustering accuracy than clustering solutions generated by the incremental genetic-based clustering ensemble algorithms using other recombination operators. …”
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A review: accuracy optimization in clustering ensembles using genetic algorithms by Ghaemi, Reza, Sulaiman, Md. Nasir, Ibrahim, Hamidah, Mustapha, Norwati

“…This paper concludes that using genetic algorithms in clustering ensemble improves the clustering accuracy and addresses open questions subject to future research.…”
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An enhanced cluster head selection algorithm for routing in mobile AD-HOC network by Abdulsaheb, Ghaida Muttasher

“…This thesis proposes a cluster based routing protocol, the Enhanced Cluster Routing Protocol (ECRP), which uses a modified cluster formation algorithm to build the cluster structure and select one of the nodes to be the cluster head. …”
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The new efficient and accurate attribute-oriented clustering algorithms for categorical data by Qin, Hongwu

“…Many algorithms for clustering categorical data have been proposed, in which attribute-oriented hierarchical divisive clustering algorithm Min-Min Roughness (MMR) has the highest efficiency among these algorithms with low clustering accuracy, conversely, genetic clustering algorithm Genetic-Average Normalized Mutual Information (G-ANMI) has the highest clustering accuracy among these algorithms with low clustering efficiency. …”
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Cluster validity of the fuzzy C-means algorithm in mammographic image using adaptive cluster & partition entropy indexes / Azwani Aziz by Aziz, Azwani

“…There are many techniques of clustering the image. The most widely used of clustering technique is Fuzzy C-Means algorithm (FCM). …”
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Adaptive persistence layer for synchronous replication (PLSR) in heterogeneous system by Beg, Abul Hashem

“…The PLSR architecture model, workflow and algorithms are described. The PLSR has been developed using Java Programming language. …”
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A study of density-grid based clustering algorithms on data streams by Amini, A., Saybani, M.R., Sahaf Yazdi, S.R.A.

“…In this paper we review the grid based clustering algorithms that use density-based algorithms or density concept for the clustering. …”
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Adaptive firefly algorithm for hierarchical text clustering by Mohammed, Athraa Jasim

“…The proposed Adaptive Firefly Algorithm (AFA) consists of three components: document clustering, cluster refining, and cluster merging. …”
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Harmony Search-Based Fuzzy Clustering Algorithms For Image Segmentation by Alia, Osama Moh’d Radi

“…However, two main issues plague these clustering algorithms: initialization sensitivity of cluster centers and unknown number of actual clusters in the given dataset. …”
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Autonomous and deterministic supervised fuzzy clustering by Lim, K.M., Loo, C.K., Lim, W.S.

“…The results obtained show that the model that uses the global k-means clustering algorithm 1 has higher accuracy when compared to a model that uses the k-means clustering algorithm. …”
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On density-based data streams clustering algorithms: A survey by Teh, Y.W.

“…Moreover, we investigate the evaluation metrics used in validating cluster quality and measuring algorithms’ performance. …”
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Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms by Teoh, Chin Chuang

“…The comparison results show that, the clusters labelled by the cluster labelling algorithm were the same as using co-spectral plot. …”
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Comparison of clustering algorithms on air quality substances in Peninsular Malaysia / Sitti Sufiah Atirah Rosly, Balkiah Moktar and Muhamad Hasbullah Mohd Razali by Rosly, Sitti Sufiah Atirah, Moktar, Balkiah, Mohd Razali, Muhamad Hasbullah

“…The output of K - means clustering algorithm shows that it can cluster the area into two clusters, namely as cluster 0 and cluster 1. …”
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An adaptive density-based method for clustering evolving data streams / Amineh Amini by Amini, Amineh

“…This study proposes a density-based algorithm for clustering evolving data streams. The proposed method, which is called MuDi-Stream (Multi Density clustering algorithm for evolving data Stream), is an online-offline algorithm with four main components. …”
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