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33 results for “Hybrid Clustering”
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Review ArticleOpen accessIn the abstractStatistical Binarization Techniques for Document Image AnalysisSaad M. Ismail, Siti Norul Huda Sheikh Abdullah, Fariza FauziBinarization is an important process in image enhancement and analysis. Currently, numerous binarization techniques have been reported in the literature. These binarization methods produce binary images from color or gray-level images. This article highlights an extensive review on various binarization approaches which are also referred to as thresholding methods. These methods are grouped into seven categories according to the employed … …Journal of Computer Science, Vol. 14, Issue 1 · 3 Jan 2018 · 8,160 accessesView PDFCite
Research ArticleOpen accessIn the abstractDocument Clustering Based on Firefly AlgorithmAthraa Jasim Mohammed, Yuhanis Yusof, Husniza HusniDocument clustering is widely used in Information Retrieval however, existing clustering techniques suffer from local optima problem in determining the k number of clusters. Various efforts have been put to address such drawback and this includes the utilization of swarm-based algorithms such as particle swarm optimization and Ant Colony Optimization. This study explores the adaptation of another swarm algorithm which … …Journal of Computer Science, Vol. 11, Issue 3 · 26 Mar 2015 · 7,510 accessesView PDFCite
Research ArticleOpen accessIn the abstractAmeliorate 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 abstractA New Cooperative Algorithm Based on PSO and K-Means for Data ClusteringMehdi Neshat, Shima Farshchian Yazdi, Daneyal Yazdani, Mehdi SargolzaeiProblem statement: Data clustering has been applied in multiple fields such as machine learning, data mining, wireless sensor networks and pattern recognition. One of the most famous clustering approaches is K-means which effectively has been used in many clustering problems, but this algorithm has some drawbacks such as local optimal convergence and sensitivity to initial points. Approach: Particle Swarm Optimization … …Journal of Computer Science, Vol. 8, Issue 2 · 19 Nov 2011 · 7,967 accessesView PDFCite
Research ArticleOpen accessIn the abstractUsing Hyper Clustering Algorithms in Mobile Network PlanningLamiaa Fattouh Ibrahim, Hesham A. SalmanProblem statement: As a large amount of data stored in spatial databases, people may like to find groups of data which share similar features. Thus cluster analysis becomes an important area of research in data mining. Applications of clustering analysis have been utilized in many fields, such as when we search to construct a cluster served by base station in … …American Journal of Applied Sciences, Vol. 8, Issue 10 · 30 Aug 2011 · 7,504 accessesView PDFCite
Research ArticleOpen accessIn the abstractEfficient Hybrid Network (Wired and Wireless) Intrusion Detection using Statistical Data Streams and Detection of Clustered AlertsP. Thangaraj, M. ThangavelProblem statement: Wireless LAN IEEE 802.11 protocols are growing rapidly and security has always been a concern with the security of wired network. Wireless networks encountered threats from unauthorized access to network resources, installation of access points and illegal sniffing (refer as classical intrusion threats). In its current hybrid wired and wireless network attacks on the generally distinguish from normal … …Journal of Computer Science, Vol. 7, Issue 9 · 30 Jul 2011 · 7,165 accessesView PDFCite
Research ArticleOpen accessIn the abstractThe Parallel Maximal Cliques Algorithm for Protein Sequence ClusteringKhalid Jaber, Nur’Aini Abdul Rashid, Rosni AbdullahProblem statement: Protein sequence clustering is a method used to discover relations between proteins. This method groups the proteins based on their common features. It is a core process in protein sequence classification. Graph theory has been used in protein sequence clustering as a means of partitioning the data into groups, where each group constitutes a cluster. Mohseni-Zadeh introduced a … …American Journal of Applied Sciences, Vol. 6, Issue 7 · 31 Jul 2009 · 7,100 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Effective Data Transformation Approach for Privacy Preserving ClusteringR. R. Rajalaxmi, A. M. NatarajanA new stream of research privacy preserving data mining emerged due to the recent advances in data mining, Internet and security technologies. Data sharing among organizations considered to be useful which offer mutual benefit for business growth. Preserving the privacy of shared data for clustering was considered as the most challenging problem. To overcome the problem, the data owner published … …Journal of Computer Science, Vol. 4, Issue 4 · 30 Apr 2008 · 7,112 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordAnchoring Public Health Forecasts: High-Precision Obesity Prevalence Estimation Via Hybrid Geodemographic Ensemble RegressionTrenton Ward, Isaac OsunmakindeObesity remains a major driver of chronic disease and rising healthcare costs in the United States. Yet, most existing predictive models rely on single-model classifiers and rarely incorporate spatial structure or ensemble-based regression, thereby limiting their ability to capture geodemographic variation. This study introduces a hybrid unsupervised–supervised ensemble framework that integrates K-Means spatial profiling with a Stacking Regressor to address … …Journal of Computer Science, Vol. 22, Issue 7 · 31 Jul 2026 · 632 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordSpatio-Temporal Anomaly Detection in Groundwater Electrical Conductivity Using a Hybrid Framework of Isolation Forest and AutoencoderEunji Lee, Seunghyun Lim, Seojun Lee, Abhijit DebnathMonitoring groundwater quality is vital for environmental safety and resource sustainability. This study combines Isolation Forest and Autoencoder models to detect anomalies in Electrical Conductivity (EC) and temperature, using monthly data collected in South Korea between 2006 and 2023. Linear regression and the Mann-Kendall test reveal a weak, episodic downward EC trend. Seasonal decomposition indicates annual cyclicality, while residual analysis … …Journal of Computer Science, Vol. 22, Issue 1 · 14 Feb 2026 · 1,918 accessesView PDFCite