Search Results - (( _ application ((means algorithm) OR (bees algorithm)) ) OR ( web applications out algorithm ))*
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A web-based implementation of k-means algorithms
Published 2022“…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. This is where k-luster comes in. k-luster, the web application developed as a result of this project, implements the K-means and K-means++ algorithm along with ten proximity measures, seven of which are distance measures and whereas the remaining three are similarity measures. …”
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Final Year Project / Dissertation / Thesis -
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A modified π rough k-means algorithm for web page recommendation system
Published 2018“…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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Thesis -
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Data clustering using the bees algorithm
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A near-optimal centroids initialization in K-means algorithm using bees algorithm
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Enhanced artificial bee colony-least squares support vector machines algorithm for time series prediction
Published 2014“…This study proposed a hybrid algorithm, based on Artificial Bee Colony (ABC) and LSSVM, that consists of three algorithms; ABC-LSSVM, lvABC-LSSVM and cmABC-LSSVM. …”
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Thesis -
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Artificial Bee Colony Algorithm for Pairwise Test Generation
Published 2017“…In a case where PABC is not at its optimal stage or its best performance, the experiments of a test case are effectively competitive. PABC progresses as a means to achieve the effective use of the artificial bee colony algorithm for pairwise testing reduction.…”
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Task scheduling in cloud computing environment using hybrid genetic algorithm and bat algorithm
Published 2022“…Furthermore, CloudSim simulator will be used to evaluate the performance of this algorithm. The result of the algorithm performance will be appeared in web application system. …”
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Academic Exercise -
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Multi objective bee colony optimization framework for grid job scheduling
Published 2013“…Grid computing is the infrastructure that involves a large number of resources like computers, networks and databases which are owned by many organizations.Job scheduling problem is one of the key issues because of high heterogeneous and dynamic nature of resources and applications in the grid computing environment.Bee colony approach has been used to solve this problem because it can be easily adapted to the grid scheduling environment.The bee algorithms have shown encouraging results in terms of time and co st.In this paper a framework for multi objective bee colony optimization is proposed to schedule batch jobs to available resources where the number of jobs is greater than the number of resources.Pareto analysis and k-means analysis are integrated in the bee colony optimization algorithm to facilitate the scheduling of jobs to resources.…”
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Application of LSSVM by ABC in energy commodity price forecasting
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A class skew-insensitive ACO-based decision tree algorithm for imbalanced data sets
Published 2021“…Ant-tree-miner (ATM) has an advantage over the conventional decision tree algorithm in terms of feature selection. However, real world applications commonly involved imbalanced class problem where the classes have different importance. …”
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An efficient fuzzy C-least median clustering algorithm
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An application of grey wolf optimizer for commodity price forecasting
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An application of hybrid swarm intelligence algorithms for dengue outbreak prediction
Published 2019“…Concerning this matter, this study presents an application of hybrid Swarm Intelligence (SI) algorithms for a dengue outbreak prediction. …”
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Structural optimization of 4-DOF agricultural robot arm
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