Search Results - (( pattern clustering algorithm ) OR ( patterns ((among algorithm) OR (ant algorithm)) ))*
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Big data clustering using grid computing and ant-based algorithm
Published 2013“…This paper presents a framework for big data clustering which utilizes grid technology and ant-based algorithm.…”
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An improved ACS algorithm for data clustering
Published 2020“…Ant colony optimisation for clustering (ACOC) is a swarm algorithm inspired by the foraging behaviour of ants. …”
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Analysis of K-Mean and X-Mean Clustering Algorithms Using Ontology-Based Dataset Filtering
Published 2021“…In this paper, we have compared the performance of K-Mean and XMean clustering algorithms using two datasets of student enrollment in higher education institutions. …”
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Optimized clustering with modified K-means algorithm
Published 2021“…Among the techniques, the k-means algorithm is the most commonly used technique for determining optimal number of clusters (k). …”
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An efficient fuzzy C-least median clustering algorithm
Published 2021“…In this paper we are discussing our new procedure for clustering called Fuzzy C-least median of squares algorithm which is an improvement to Fuzzy C-means (FCM) algorithm. …”
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Modeling of vehicle trajectory clustering based on LCSS for traffic pattern extraction
Published 2017“…The implementation of k-means and fuzzy c-means (FCM) clustering algorithm for vehicle flow analyzing task is served as focus in this paper. …”
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Proceedings -
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Partitional clustering algorithms for highly similar and sparseness y-short tandem repeat data / Ali Seman
Published 2013“…Six Y-STR data sets were used as a benchmark to evaluate the performances of the algorithm against the other eight partitional clustering algorithms. …”
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A survey: Challenges of image segmentation based fuzzy c-means clustering algorithm
Published 2024journal::journal article -
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STATISTICAL FEATURE LEARNING THROUGH ENHANCED DELAUNAY CLUSTERING AND ENSEMBLE CLASSIFIERS FOR SKIN LESION SEGMENTATION AND CLASSIFICATION
Published 2021“…Moreover, skin lesion images are clustered based on fused color, pattern and shape based features. …”
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A framework of modified adaptive neuro-fuzzy inference engine
Published 2012“…The Takagi-Sugeno-Kang (TSK) type fuzzy inference system was chosen and constructed by an automatic generation of clusters as well as membership functions and minimal rules through the use of hybrid fuzzy clustering and the modified apriori algorithms respectively. …”
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12
A guided hybrid k-means and genetic algorithm models for children handwriting legibility performance assessment / Norzehan Sakamat
Published 2021“…Size was extracted using Extreme Point Detection algorithm and Hit or Miss Transformation method was used to extract the stroke formation pattern. …”
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Music Recommender System Using Machine Learning Content-Based Filtering Technique
Published 2022“…These algorithms identify hidden patterns or data groupings without the assistance of a human. …”
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Undergraduates Project Papers -
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Clustering of large time-series datasets using a multi-step approach / Saeed Reza Aghabozorgi Sahaf Yazdi
Published 2013“…It overcomes the limitations of conventional clustering algorithms in dealing with time-series data. …”
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15
Design of intelligent Qira’at identification algorithm
Published 2017“…The process of the SPAP Algorithm is to extend parameters of the Affine Projection Block with two different selections of windowing length that affect the final accuracy on pattern classification. …”
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Facilitating resource allocation decision through Bibliomining: the case of UTM's library / Md Razib Karno
Published 2015“…The data mining technique was adopted to explore the relationship among statistically patterned and clustered bibliographic data. …”
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Dietary patterns and health outcomes among African American maintenance hemodialysis patients
Published 2020“…Implausible energy intake reports were screened out by comparing reported energy intake (rEI) with predicted total energy expenditure (pTEE). Cluster analysis, using the k-means algorithm, identified two distinct dietary patterns in the study population: a high “sugar sweetened beverage” pattern (hiSSB) and a low “sugar sweetened beverage pattern” (loSSB). …”
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Incremental continuous ant colony optimization for tuning support vector machine’s parameters
Published 2013“…Support Vector Machines are considered to be excellent patterns classification techniques. The process of classifying a pattern with high classification accuracy counts mainly on tuning Support Vector Machine parameters which are the generalization error parameter and the kernel function parameter.Tuning these parameters is a complex process and Ant Colony Optimization can be used to overcome the difficulty. …”
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Development and characterization of anonymous nuclear markers to determine genetic variation in two groupers species and their hybrids
Published 2015“…Among these 13 E. lanceolatus and E. fuscoguttatus ncni-ANM loci ranged in size from 153 to 177 bp and 157 to 624 bp respectively revealing variation across all OTUs through visualization of agarose gel electrophoresis patterns and binary matrix scoring. …”
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Face emotion recognition using artificial intelligence techniques
Published 2008“…It is found, from the optimized data, that there is no common pattern to recognize emotions within among the three subjects. …”
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