Search Results - (( java implementation clustering algorithm ) OR ( knowledge data optimization algorithm ))
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Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…This project will use fuzzy k-means clustering algorithm to cluster the data because it is easy to implement and have many advantages. …”
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Thesis -
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Image clustering comparison of two color segmentation techniques
Published 2010“…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. …”
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A Toolkit for Simulation of Desktop Grid Environment
Published 2014“…A simulator for desktop grid environment has been developed using Java as the implementation language due to its wide popularity. …”
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Final Year Project -
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A web-based implementation of k-means algorithms
Published 2022“…Firstly, k-luster could incorporate additional clustering algorithms, or even classification algorithms in the future. …”
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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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Conference or Workshop Item -
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A near-optimal centroids initialization in K-means algorithm using bees algorithm
Published 2009“…This creates problem for novice users especially to those who have no or little knowledge on the data.Trial-error attempt might be one of the possible preference to deal with this issue.In this paper, an optimization algorithm inspired from the bees foraging activities is used to locate near-optimal centroid of a given data set.Result shows that propose approached prove it robustness and competence in finding a near optimal centroid on both synthetic and real data sets.…”
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Clustering chemical data set using particle swarm optimization based algorithm
Published 2008“…We found that PSO algorithm reveals better performance than Ward’s algorithm on continuous data format; however for binary data format, Ward’s algorithm outperforms arrogantly.…”
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A Conceptual Framework of Bacterial Foraging Optimization Algorithm for Data Classification
Published 2016“…Most previous works on Bacterial Foraging Optimization Algorithm (BFOA) for data classification were integrated BFOA as a feature selection algorithm and parameters optimizer for other classifiers. …”
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Proceeding -
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Document clustering for knowledge discovery using nature-inspired algorithm
Published 2014“…As the internet is overload with information, various knowledge based systems are now equipped with data analytics features that facilitate knowledge discovery.This includes the utilization of optimization algorithms that mimics the behavior of insects or animals.This paper presents an experiment on document clustering utilizing the Gravitation Firefly algorithm (GFA).The advantage of GFA is that clustering can be performed without a pre-defined value of k clusters.GFA determines the center of clusters by identifying documents with high force.Upon identification of the centers, clusters are created based on cosine similarity measurement.Experimental results demonstrated that GFA utilizing a random positioning of documents outperforms existing clustering algorithm such as Particles Swarm Optimization (PSO) and K-means.…”
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Multilingual Sentiment Analysis From Students Feedback: Optimal Techniques And Resources For Bengali Lingual Data
Published 2024thesis::doctoral thesis -
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A hybrid controller method with genetic algorithm optimization to measure position and angular for mobile robot motion control
Published 2023“…Yet, current approaches face problems in managing unstructured gain data and producing accurate local planning due to the lack of formulation in the knowledge on the gain optimization. …”
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A hybrid controller method with genetic algorithm optimization to measure position and angular for mobile robot motion control
Published 2023“…Yet, current approaches face problems in managing unstructured gain data and producing accurate local planning due to the lack of formulation in the knowledge on the gain optimization. …”
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A hybrid controller method with genetic algorithm optimization to measure position and angular for mobile robot motion control
Published 2023“…Yet, current approaches face problems in managing unstructured gain data and producing accurate local planning due to the lack of formulation in the knowledge on the gain optimization. …”
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A hybrid controller method with genetic algorithm optimization to measure position and angular for mobile robot motion control
Published 2023“…Yet, current approaches face problems in managing unstructured gain data and producing accurate local planning due to the lack of formulation in the knowledge on the gain optimization. …”
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A hybrid controller method with genetic algorithm optimization to measure position and angular for mobile robot motion control
Published 2022“…Yet, current approaches face problems in managing unstructured gain data and producing accurate local planning due to the lack of formulation in the knowledge on the gain optimization. …”
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A hybrid controller method with genetic algorithm optimization to measure position and angular for mobile robot motion control
Published 2023“…Yet, current approaches face problems in managing unstructured gain data and producing accurate local planning due to the lack of formulation in the knowledge on the gain optimization. …”
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A hybrid controller method with genetic algorithm optimization to measure position and angular for mobile robot motion control
Published 2023“…Yet, current approaches face problems in managing unstructured gain data and producing accurate local planning due to the lack of formulation in the knowledge on the gain optimization. …”
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A hybrid controller method with genetic algorithm optimization to measure position and angular for mobile robot motion control
Published 2023“…Yet, current approaches face problems in managing unstructured gain data and producing accurate local planning due to the lack of formulation in the knowledge on the gain optimization. …”
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