Search Results - (( java implementation cell algorithm ) OR ( programming process clustering algorithm ))
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Data mining in network traffic using fuzzy clustering
Published 2003“…The fuzzy clustering process are made using three algorithms : Fuzzy C-Means (FCM), Gustafsof-Kessel (GK) and Gath-Geva (GG) algorithm. …”
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Data mining in network traffic using fuzzy clustering
Published 2003“…The fuzzy clustering process are made using three algorithms : Fuzzy C-Means (FCM), Gustafsof-Kessel (GK) and Gath-Geva (GG) algorithm. …”
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Fuzzy subtractive clustering (FSC) with exponential membership function for heart failure disease clustering
Published 2022“…Objective: Fuzzy clustering algorithm is a partition method used to assign objects from a data set to a cluster by marking the average location. …”
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Learning analytic framework for students’ academic performance and critical learning pathways
Published 2024“…The resulting reduced dataset is then subjected to various clustering algorithms, including partition-based clustering (K-means), hierarchical clustering, and density-based clustering (DBSCAN). …”
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K Nearest Neighbor Joins And Mapreduce Process Enforcement For The Cluster Of Data Sets In Bigdata
Published 2018“…K Nearest Neighbor Joins (KNN join) are regarded as highly primitive and expensive operations in the data mining.The efficient use of KNN join has proven good results in finding the objects from two data sets prevailed in the huge databases.This has been achieved with the combination of K-Nearest Neighbor query and join operation to find the distinct objects from different data sets.MapReduce is a newly introduced program with the combination of Map Procedure method and Reduce Method widely used in BigData.MapReduce is enriched with parallel distributed algorithm to find the results on a cluster of data sets in BigData.In this paper,the combination of KNN join and MapReduce methods are utilized on the cluster of data sets in BigData for knowledge discovery.Exploring the pinpoint data from huge data sets stored in Big Data demands the distributed large scale data processing.The present research paper is focusing on generic steps for KNN joins exploration operations on MapReduce.The operations of KNN Join are targeted to perform the data partitioning and data pre-processing and necessary calculations.By utilizing the combination of KNN joins with MapReduce methods on BigData data sets will demonstrate a solution for complex computational analysis. …”
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Chaotic mutation immune evolutionary programming for photovoltaic planning in power system / Sharifah Azma Syed Mustaffa
Published 2020“…Further research was done on the cluster formation of DGPV installation from the obtained results. …”
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A Multi-Criteria Decision-Making Approach for Targeted Distribution of Smart Indonesia Card (KIP) Scholarships
Published 2025“…Second, the clustering process was conducted to group the priorities of prospective scholarship recipients using the K-Means and K-Medoids methods, as well as a combination of PCA+K-Means and PCA+K-Medoids. …”
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Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform
Published 2009“…The development of this architecture is based on several programming language as it involves algorithm implementation on C, parallelization using Parallel Virtual Machine (PVM) and Java for web services development. …”
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Effective software fault localization based on complex network theory / Abubakar Zakari
Published 2019“…Fault localization plays a vital role in the debugging process, and it is also the most tedious and expensive activity in program debugging. …”
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Feature clustering for pso-based feature construction on high-dimensional data
Published 2019“…The Redundancy-Based Feature Clustering (RFC) algorithm was applied to choose the most informative features from the original data, while PSO was used to construct new features from those selected by RFC. …”
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Parallel Implementation of Two Level Barotropic Models Applied to the Weather Prediction Problem
Published 2004“…Then the parallel algorithms are constructed and run using the Beowulf Cluster machine. …”
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Implementation of Hybrid Indexing, Clustering and Classification Methods to Enhance Rural Development Programme in South Sulawesi
Published 2024“…The Fuzzy Tsukamoto and Smallest of Maximum methods were then used to classify villages into less development, which involved CSLI-Clusters as indicators. Using the cosine similarity algorithm for knowledge recommendation is village identified, utilizing community feedback as the foundation. …”
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Regionalization by fuzzy expert system based approach optimized by genetic algorithm.
Published 2013“…In recent years soft computing methods are being increasingly used to model complex hydrologic processes. These methods can simulate the real life processes without prior knowledge of the exact relationship between their components. …”
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A Framework for Green Energy Resources Identification and Integration Supported by Real-Time Monitoring, Control, and Automation Applications
Published 2025“…The process involved clustering by divisions and designing optimal electrical power line routing for each cluster, prioritizing minimum total distance, elevation difference, and average ground flash density. …”
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