Research ArticleOpen accessEvery word in the titleImproving Clustering Robustness through Fuzzy Ensemble of K-Means and Mean ShiftLNC. Prakash K., Palamakula Ramesh Babu, Shaik Thaseentaj et al.Ensemble clustering has emerged as a powerful strategy to improve the robustness and accuracy of unsupervised learning, particularly when individual algorithms struggle with noisy, heterogeneous, or high-dimensional data. This study introduces a fuzzy-based ensemble approach that integrates the complementary strengths of K-Means and Mean Shift clustering, followed by fuzzy membership assignment for data points that remain ambiguous. The inclusion of … …Journal of Computer Science, Vol. 22, Issue 5 · 20 May 2026 · 1,257 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Fuzzy Clustering Based Method for the Spatio-Temporal Data AnalysisAnahita Zolghadr, Afsaneh JalalianSpatiotemporal data is a type of data that is collected by the sensors. This type of data has two spatial and temporal dimensions. There are many challenges in analyzing spatiotemporal big data. Common evaluation metrics of clustering methods are not appropriate for spatiotemporal data. Previous clustering methods and the conventional evaluation metrics are efficient for data like time series with … …Journal of Computer Science, Vol. 18, Issue 6 · 13 Jun 2022 · 5,638 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleEffect of Clustering in Designing a Fuzzy Based Hybrid Intrusion Detection System for Mobile Ad Hoc NetworksD. Vydeki, R. S. BhuvaneswaranIntrusion Detection System (IDS) provides additional security for the most vulnerable Mobile Adhoc Networks (MANET). Use of Fuzzy Inference System (FIS) in the design of IDS is proven to be efficient in detecting routing attacks in MANETs. Clustering is a vital means in the detection process of FIS based hybrid IDS. This study describes the design of such a system … …Journal of Computer Science, Vol. 9, Issue 4 · 14 May 2013 · 6,469 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleArtificial Bee Colony Algorithm Integrated with Fuzzy C-mean Operator for Data ClusteringM. Krishnamoorthi, A. M. NatarajanClustering task aims at the unsupervised classification of patterns in different groups. To enhance the quality of results, the emerging swarm-based algorithms now-a-days become an alternative to the conventional clustering methods. In this study, an optimization method based on the swarm intelligence algorithm is proposed for the purpose of clustering. The significance of the proposed algorithm is that it uses … …Journal of Computer Science, Vol. 9, Issue 4 · 6 May 2013 · 6,299 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleAmeliorate Fuzzy C-Means: An Ameliorate Fuzzy C-Means Clustering Algorithm for CT-Lung Image SegmentationJ. Bridget Nirmala, S. GowriEffective and efficient image segmentation acts as a preliminary stage for the computer-aided diagnosis of medical images. For image segmentation, many FCM-based clustering techniques have been proposed. Regrettably, the existing FCM technique does not generate accurate and standardized segmentation results. This is due to the noise present in the image as well as the random initialization of membership values for … …American Journal of Applied Sciences, Vol. 10, Issue 11 · 1 Oct 2013 · 6,819 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA HYBRID FIREFLY ALGORITHM WITH FUZZY-C MEAN ALGORITHM FOR MRI BRAIN SEGMENTATIONMutasem K. AlsmadiImage processing is one of the essential tasks to extract suspicious region and robust features from the Magnetic Resonance Imaging (MRI). A numbers of the segmentation algorithms were developed in order to satisfy and increasing the accuracy of brain tumor detection. In the medical image processing brain image segmentation is considered as a complex and challenging part. Fuzzy c-means is … …American Journal of Applied Sciences, Vol. 11, Issue 9 · 10 Sep 2014 · 8,074 accessesView PDFCite
Research ArticleOpen accessIn the keywordsTWO PHASE CLUSTERING METHOD FOR LEACH PROTOCOL FOR EFFECTIVE CLUSTER HEAD SELECTIONRathi, ViswanathanA Wireless Sensor Networks (WSN) comprise of a huge quantity of clusters of sensor nodes that can inter communicate with all nodes and with the base station through a wireless link. All clusters are corresponding to a cluster head to provide a direct communication to the base station and in addition with other cluster heads. Obviously well-organized selection of cluster … …Journal of Computer Science, Vol. 10, Issue 3 · 21 Nov 2013 · 7,122 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAn Overview of Research Challenges for Classification of Cardiotocogram DataC. Sundar, M. Chitradevi, G. GeetharamaniCardiotocography (CTG) is a simultaneous recording of Fetal Heart Rate (FHR) and Uterine Contractions (UC). The most common diagnostic techniques to evaluate maternal and fetal well-being during pregnancy and before delivery. By observing the Cardiotocography trace patterns doctors can understand the state of the fetus. There are several signal processing and computer programming based techniques for interpreting a typical Cardiotocography … …Journal of Computer Science, Vol. 9, Issue 2 · 2 Apr 2013 · 7,827 accessesView PDFCite
Research ArticleOpen accessIn the keywordsFuzzy Based Secure Data Aggregation Technique in Wireless Sensor NetworksD. HevinRajesh, B. ParamasivanProblem statement: Secure data aggregation is a challenging task in wireless sensor network due to the facts like more complexity, greater overhead in the case of cryptographic techniques. These issues need to be overcome using efficient technique. Approach: We propose a fuzzy based secure data aggregation technique which was having 3 phases. In its first phase, it performs clustering and … …Journal of Computer Science, Vol. 8, Issue 6 · 17 Mar 2012 · 7,252 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Rough Set based Gene Expression Clustering AlgorithmJ. Jeba Emilyn, K. RamarProblem statement: Microarray technology helps in monitoring the expression levels of thousands of genes across collections of related samples. Approach: The main goal in the analysis of large and heterogeneous gene expression datasets was to identify groups of genes that get expressed in a set of experimental conditions. Results: Several clustering techniques have been proposed for identifying gene signatures and … …Journal of Computer Science, Vol. 7, Issue 7 · 28 Jun 2011 · 6,830 accessesView PDFCite