Search Results - (( java implementation modified algorithm ) OR ( pattern solution clustering algorithm ))
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Clustering ensemble learning method based on incremental genetic algorithms
Published 2012“…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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Direct approach for mining association rules from structured XML data
Published 2012“…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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An improved ACS algorithm for data clustering
Published 2020“…Data clustering is a data mining technique that discovers hidden patterns by creating groups (clusters) of objects. …”
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A partition based feature selection approach for mixed data clustering / Ashish Dutt
Published 2020“…One such pre-processing algorithm in EDM is clustering. It is a widely used method in data mining to discover unique patterns in underlying data. …”
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Trajectory pattern mining via clustering based on similarity function for transportation surveillance
Published 2016“…This grouping task is called as clustering. Each of the clusters formed represents a pattern. …”
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Minimizing the number of stunting prevalence using the euclid algorithm clustering approach
Published 2023“…The algorithm used is Euclid. The Euclid algorithm can cluster stunting prevalence data into 4 clusters with the very little category at 79%, the little category at 67%, the many categories at 51%, and the very much category at 21%. …”
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A modified π rough k-means algorithm for web page recommendation system
Published 2018“…Hence, this study carried out several objectives to augment the support of modified clustering algorithm. Firstly, an extended K-Means clustering algorithm (called X-Means algorithm) is proposed to filter/remove the noise from user session data to eliminate outliers or irrelevant pages. …”
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A comprehensive 3-phase framework for determining the customer’s product usage in a food supply chain
Published 2022“…Moreover, the efficiency of the outcomes is evaluated using the Silhouette Coefficient, indicating that the proposed algorithm could provide solutions with a 68% score. …”
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A numerical method for frequent pattern mining
Published 2009“…A reasonable solution is identifying maximal frequent patterns which form the smallest representative set of patterns to generate all frequent patterns. …”
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OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT
Published 2023“…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. The objectives of this work are: i) to provide a comprehensive review of the cloud and scheduling process; ii) to classify the scheduling strategies and scientific workflows; iii) to implement our proposed algorithm with various scheduling algorithms (i.e., Min-Min, Round-Robin, Max-Min, and Modified Max-Min) for performance comparison, within different cloudlet sizes (i.e., small, medium, large, and heavy) in three scientific workflows (i.e., Montage, Epigenomics, and SIPHT); and iv) to investigate the performance of the implemented algorithms by using CloudSim. …”
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Application of Optimization Methods for Solving Clustering and Classification Problems
Published 2011“…Next the problem of data classification is studied as a problem of global, non-smooth and non-convex optimization; this approach consists of describing clusters for the given training sets. The data vectors are assigned to the closest cluster and correspondingly to the set, which contains this cluster and an algorithm based on a derivative-free method is applied to the solution of this problem. …”
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A derivative-free optimization method for solving classification problem
Published 2010“…Approach: The problem of data classification was studied as a problem of global, nonsmooth and nonconvex optimization; this approach consists of describing clusters for the given training sets. The data vectors are assigned to the closest cluster and correspondingly to the set, which contains this cluster and an algorithm based on a derivative-free method is applied to the solution of this problem. …”
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Prevention And Detection Mechanism For Security In Passive Rfid System
Published 2013“…The proposed protocol is designed with lightweight cryptographic algorithm, including XOR, Hamming distance, rotation and a modified linear congruential generator (MLCG). …”
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Automatic generation of content security policy to mitigate cross site scripting
Published 2016“…It can be extended to support generating CSP for contents that are modified by JavaScript after loading. Current approach inspects the static contents of URLs.…”
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Spatial-temporal analysis using two-stage clustering and GIS-based MCDM to identify potential market regions
Published 2021“…Subsequently, the origin schools' regencies/cities were clustered using the k- prototypes algorithm based on their time-series pattern category, the consistency in sending students, average cumulative grade point average (CGPA), and dropout (DO) rate. …”
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A guided hybrid k-means and genetic algorithm models for children handwriting legibility performance assessment / Norzehan Sakamat
Published 2021“…K-Means algorithm a popular efficient clustering techniques and genetic algorithm a widely used evolutionary algorithm and known for its adaptive nature were combined to determine the level of handwriting legibility for each child. …”
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Profiling network traffic of Sultan Idris Shah building (BSIS) using data mining technique / Rusmawati Ishak
Published 2018“…Orange is a tool that being used in implementing K-Means Clustering Algorithm that could be seen as the most suitable solution to find a network trend pattern of user accessing the Internet and to produce with profiling network. …”
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