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Initialization Methods For Conventional Fuzzy C-Means And Its Application Towards Colour Image Segmentation
Published 2011“…Due to its capability in providing a particularly promising solution to clustering problems, the conventional Fuzzy C-Mean (FCM) algorithm is widely used as a segmentation method. …”
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Clustering ensemble learning method based on incremental genetic algorithms
Published 2012“…In addition, experiments prove that incremental genetic-based clustering ensemble algorithm speed up to converge into an optimal clustering solution, where pattern ensemble learning method and the cluster partitions produced by the threshold fuzzy c-means clustering algorithm are employed as recombination operator and initial population, respectively.…”
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Efficient genetic partitioning-around-medoid algorithm for clustering
Published 2019“…These algorithms mostly built upon the partitioning k-means clustering algorithm. …”
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Application of intelligence based genetic algorithm for job sequencing problem on parallel mixed-model assembly line
Published 2010“…Then, it started to find the best sequence of jobs for each line based on the generated population by heuristic algorithm. By this means, intelligence based genetic algorithm only concentrated on those initial populations that produce better solutions instead of probing the entire search space. …”
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Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm
Published 2025“…The results showed that using canopy as a preprocessing step cut the time it proceeds to deal with the significant number of power load abnormalities found in parallel using a fast density peak dataset and the time it proceeds for the k-means algorithm to run. Additionally, tests demonstrate that combining canopy and the K-means algorithm to analyze data performs consistently and dependably on the Hadoop platform and has a clustering result that offers a scalable and effective solution for power system monitoring. ? …”
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An effective and novel wavelet neural network approach in classifying type 2 diabetics
Published 2012“…In this paper, we propose a novel enhanced fuzzy c-means clustering algorithm – specifically, the modified point symmetry-based fuzzy c-means (MPSDFCM) algorithm – in initializing the translation vectors of the WNNs. …”
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Enhancing clustering algorithm with initial centroids in tool wear region recognition
Published 2020“…Nevertheless, the algorithm is sensitive to the initial centroids giving various solution every time the system updating. …”
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A Modified LRE-TL Real-Time Multiprocessor Scheduling Algorithm
Published 2013“…We have conducted an independent-samples t test to compare tasks migration using the original LRE-TL algorithm and the modified algorithm. The results obtained showed that there was a significance reduction in tasks migration when the proposed solution is applied.…”
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A modified LRE-TL real-time multiprocessor scheduling algorithm
Published 2014“…We have conducted an independent-samples t-test to compare tasks migration using the original LRE-TL algorithm and the modified algorithm. The results obtained showed that there was a significance reduction in tasks migration when the proposed solution is applied. …”
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Solving computational algorithm using CLONALNet technique based on artificial clonal selection
Published 2023“…CLONALNet enforces an algorithm that is much more robust in evaluating the fitness for each antibody cells since it initiates boundaries so that the initialization process doesn't run off as of previous CLONALG algorithm but still maintains the immune network interaction as in aiNet. …”
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Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources
Published 2021“…Herschel-Bulkley model is used to approximate the complex rheological behavior of a non-Newtonian fluid. The proposed DNN algorithm is structured to incorporate initial/boundary conditions in cylindrical coordinates and approximate the solution without the aid of any simulated or training data. …”
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A guided hybrid k-means and genetic algorithm models for children handwriting legibility performance assessment / Norzehan Sakamat
Published 2021“…The combined method is called Hybrid K-MeansCGA. Modifications of K-Means structures were done by inserting genetic algorithm operators and tuning the population. …”
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Modeling of vanillin adsorption from aqueous solution using resin H103 by artificial neural network
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Cr(VI) adsorption from aqueous solution by an agricultural waste based carbon
Published 2016“…The effects of pH, contact time, initial Cr(vi) concentration and adsorbent dose on the adsorption of Cr(vi) from aqueous solution were investigated. …”
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A new variant of black hole algorithm based on multi population and levy flight for clustering problem
Published 2020“…Black Hole (BH) optimization algorithm has been underlined as a solution for data clustering problems. …”
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Hybrid dynamic scheduling model for flexible manufacturing system with machine availability and new job arrivals
Published 2015“…The statistical analyses demonstrate the efficiency and effectiveness of the proposed hybrid BBO-VNS algorithm over GA, BBO and PBSA to find optimum/near optimum solutions within reasonable amount of time. …”
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Fuzzy clustering method and evaluation based on multi criteria decision making technique
Published 2018“…For the third problem a modified of Kohonen Network (MKN) algorithm was proposed to select the initial centres of clusters. …”
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Performance of amidoxime-modified poly(acrylonitrile- Co-acrylic acid) for removal of boron in aqueous solution
Published 2019“…Among several models, radial basis function (RBF) with orthogonal least square (OLS) algorithm displays good prediction on boron adsorption behaviour with mean square error (MSE) and coefficient of determination (R²) at 0.000209 and 0.9985, respectively. …”
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