Sign inSubmit
Tips: “quotes” for a phrase · author:Lee · a DOI goes straight to its article

79 articles for “clustering algorithms”
Set a search alert
Research ArticleOpen accessPhrase in the titleReal-Time Simulation Method Using Monte Carlo and Clustering Algorithms: A Case Study Covering Drill Bit WearRodolfo Wilvert Reitz, Paulo José de Freitas FilhoMinimization of the cost of drilling an oil well is primarily achieved by reducing the operation completion time, which in turn can be achieved by increasing the Rate of Penetration (ROP). The ROP is the result of a combination of factors, such as lithological formation, operational parameters and bit wear. This paper addresses bit wear during drilling, using a method … …Journal of Computer Science, Vol. 14, Issue 2 · 27 Feb 2018 · 8,210 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleImproving the Performance of Multivariate Bernoulli Model based Documents Clustering Algorithms using Transformation TechniquesPerumal Pitchandi, Nedunchezhian RajuProblem statement: Document clustering is the most important areas of data mining since they are very much and currently the subject of significant global research since such areas strengthen the enterprises of web intelligence, web mining, web search engine design and so forth. Generative models based on the multivariate Bernoulli and multinomial distributions have been widely used for text classification. … …Journal of Computer Science, Vol. 7, Issue 5 · 7 May 2011 · 7,281 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleCOMPARATIVE STUDY OF K-MEANS AND K-MEANS++ CLUSTERING ALGORITHMS ON CRIME DOMAINBashar Aubaidan, Masnizah Mohd, Mohammed AlbaredThis study presents the results of an experimental study of two document clustering techniques which are k-means and k-means++. In particular, we compare the two main approaches in crime document clustering. The drawback of k-means is that the user needs to define the centroid point. This becomes more critical when dealing with document clustering because each center point represented by … …Journal of Computer Science, Vol. 10, Issue 7 · 19 Feb 2014 · 7,762 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleContent Based Medical Image Retrieval with Texture Content Using Gray Level Co-occurrence Matrix and K-Means Clustering AlgorithmsB. Ramamurthy, K. R. ChandranProblem statement: Recently, there has been a huge progress in collection of varied image databases in the form of digital. Most of the users found it difficult to search and retrieve required images in large collections. In order to provide an effective and efficient search engine tool, the system has been implemented. In image retrieval system, there is no methodologies … …Journal of Computer Science, Vol. 8, Issue 7 · 24 May 2012 · 7,448 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleComputational Complexity between K-Means and K-Medoids Clustering Algorithms for Normal and Uniform Distributions of Data PointsT. Velmurugan, T. SanthanamProblem statement: Clustering is one of the most important research areas in the field of data mining. Clustering means creating groups of objects based on their features in such a way that the objects belonging to the same groups are similar and those belonging to different groups are dissimilar. Clustering is an unsupervised learning technique. The main advantage of clustering … …Journal of Computer Science, Vol. 6, Issue 3 · 31 Mar 2010 · 19,434 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleDetecting Anomalies in IoT Using Intuitionistic Fuzzy Clustering AlgorithmsVijo Arul Selvi M., Fehmin Nadira Laskar, Fokrul Alom Mazarbhuiya et al.Intuitionistic Fuzzy Sets (IFS) are convenient ways to represent the vagueness and uncertainty inherent in any dataset. There are many uses of these. One such use is the Fuzzy C-Means (FCM) algorithm, which clusters the data objects into a pre-assigned (c) number of fuzzy clusters, which has been adopted in many fields, namely, pattern classification, anomaly detection, fraud identification, etc. … …Journal of Computer Science, Vol. 22, Issue 2 · 2 Mar 2026 · 1,600 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleNewcastle Traffic Classification Using Clustering AlgorithmsHamad B Matar, Talal Almutairi, Nayef Z Al-MutairiThe urban road traffic network evolution is complex and varies depend on road type, zoning types and social activities. Typical traffic pattern variation of road network could be examined by considering the daily human travel activities. Thus, factor and cluster analysis is carried out. This paper is a comparative analysis of various Data Mining clustering methods for the grouping of … …American Journal of Engineering and Applied Sciences, Vol. 13, Issue 2 · 4 Apr 2020 · 7,214 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleUsing 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
Literature ReviewOpen accessEvery word in the titleAdvances in Document Clustering with Evolutionary-Based AlgorithmsSarmad Makki, Razali Yaakob, Norwati Mustapha, Hamidah IbrahimDocument clustering is the process of organizing a particular electronic corpus of documents into subgroups of similar text features. Formerly, a number of conventional algorithms had been applied to perform document clustering. There are current endeavors to enhance clustering performance by employing evolutionary algorithms. Thus, such endeavors became an emerging topic gaining more attention in recent years. The aim of … …American Journal of Applied Sciences, Vol. 12, Issue 10 · 20 Oct 2015 · 7,186 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleSegmentation of Medical Image using Clustering and Watershed AlgorithmsM.C. Jobin Christ, R.M.S. ParvathiProblem statement: Segmentation plays an important role in medical imaging. Segmentation of an image is the division or separation of the image into dissimilar regions of similar attribute. In this study we proposed a methodology that integrates clustering algorithm and marker controlled watershed segmentation algorithm for medical image segmentation. The use of the conservative watershed algorithm for medical image analysis … …American Journal of Applied Sciences, Vol. 8, Issue 12 · 22 Oct 2011 · 8,780 accessesView PDFCite