Search Results - (( processes evaluation clustering algorithm ) OR ( java simulation optimization algorithm ))

Adaptive grid-meshed-buffer clustering algorithm for outlier detection in evolving data stream by Abdulateef, Alaa Fareed

“…Evaluation was made based on various evaluation metrics related to outlier detection and clustering quality. …”
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An online density-based clustering algorithm for data stream based on local optimal radius and cluster pruning by Islam, Md Kamrul

“…These results prove the superiority of BOCEDS algorithm over the existing clustering algorithms. …”
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

“…The simulation is implemented with iFogSim and java programming language. …”
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Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms by Alswaitti, Mohammed Y. T.

“…The latter drawbacks are consequences of the difficulty in balancing the exploration and exploitation processes which directly affect the final quality of the clustering solutions. …”
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Fuzzy clustering method and evaluation based on multi criteria decision making technique by Sameer, Fadhaa Othman

“…The proposed algorithm is used as a pre-processing method for data followed by Gustafson-Kessel (GK) algorithm to classify credit scoring data. …”
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Modeling and Analysis of New Hybrid Clustering Technique for Vehicular Ad Hoc Network by Abdulrazzak H.N., Hock G.C., Mohamed Radzi N.A., Tan N.M.L., Kwong C.F.

“…The effectiveness of the clustering model is the most important challenge. The K-Means clustering algorithm is an effective algorithm for multi-clusters that can be used in VANETs. …”

Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

“…Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources. A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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Parallel genetic algorithms for shortest path routing in high- performance computing / Mohd Erman Safawie Che Ibrahim by Che Ibrahim, Mohd Erman Safawie

“…The objectives of this project to set-up Beowulf cluster computer to apply the Travelling Salesman Problem in parallel by using Genetic Algorithms and evaluate sequential algorithms and parallel algorithms by Genetic Algorithms. …”
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Ant colony optimization algorithm for load balancing in grid computing by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

“…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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The Parallel Fuzzy C-Median Clustering Algorithm Using Spark for the Big Data by Mallik, Moksud Alam, Zulkurnain, Nurul Fariza, Siddiqui, Sumrana, Sarkar, Rashel

“…In the partitioning phase, the data is partitioned into smaller subsets that can be clustered in parallel across multiple nodes. The suggested method, implemented in the Databricks cloud platform provides high clustering accuracy, as measured by clustering evaluation metrics such as the silhouette coefficient, cost function, partition index, clustering entropy. …”
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Integrated bisect K-means and firefly algorithm for hierarchical text clustering by Mohammed, Athraa Jasim, Yusof, Yuhanis, Husni, Husniza

“…At each level of the proposed Bisect FA, firefly algorithm works to produce the best clusters. For evaluation purposes, we performed experiments on 20 newsgroups dataset that is commonly used in text clustering studies.The results demonstrate that Bisect FA obtains more accurate and compact clustering than Bisect K-means, K-means and C-firefly algorithms. …”
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On density-based data streams clustering algorithms: A survey by Teh, Y.W.

“…Moreover, we investigate the evaluation metrics used in validating cluster quality and measuring algorithms’ performance. …”
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A soft hierarchical algorithm for the clustering of multiple bioactive chemical compounds by Salim, Naomie, Shah, J. Z.

“…In this work a fuzzy hierarchical algorithm is developed which provides a mechanism not only to benefit from the fuzzy clustering process but also to get advantage of the multiple membership function of the fuzzy clustering. …”
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Towards lowering computational power in IoT systems: Clustering algorithm for high-dimensional data stream using entropy window reduction by Alkawsi G., Al-amri R., Baashar Y., Ghorashi S., Alabdulkreem E., Kiong Tiong S.

“…The findings of the experiments are compared to the outcomes of BOCEDS, CEDAS, and MuDi-Stream algorithms. The outcomes indicate that the EWR algorithm outperformed the baseline clustering algorithms. …”

Biological-based semi-supervised clustering algorithm to improve gene function prediction by Kasim, Shahreen, Deris, Safaai, M. Othman, Razib, Hashim, Rathiah

“…However, commonclustering algorithms do not provide a comprehensive approach that look into the three categories of annotations; biologicalprocess, molecular function, and cellular component, and were not tested with different functional annotation database formats.Furthermore, the traditional clustering algorithms use random initialization which causes inconsistent cluster generation and areunable to determine the number of clusters involved. …”
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Clustering of Chemical Compounds using Unsupervised Neural Networks Algorithms: a comparison by Zeb Shah, Jehan, Salim, Naomie

“…Clustering of chemical databases has tremendous significance in the process of compound selection, virtual screening and in the drug designing and discovery process as a whole. …”
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Segmentation of MRI brain images using statistical approaches by Balafar, Mohammad Ali

“…Moreover, three improvements of EM for brain MRI segmentation are proposed, which incorporate neighbourhood information in a new manner in the clustering process. In addition, two algorithms for the post-processing of clustering results using user-interaction and the re-evaluation of boundary data in each cluster are presented. …”
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Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition by Leong, Shi Xiang

“…Phase 1 is mainly to evaluate the performance of clustering algorithm (K-Means and FCM). …”
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Clustering of chemical compounds using unsupervised neural networks algorithms : a comparison by Zeb Shah, Jehan, Salim, Naomie

“…Clustering of chemical databases has tremendous significance in the process of compound selection, virtual screening and in the drug designing and discovery process as a whole. …”
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An Efficient Cluster Head Election Algorithm for Client Mesh Networks using Fuzzy Logic Control by Adekiigbe, Adebanjo, Ahmed, Abdulghani Ali, Sadiq, Ali Safa, Ghafoor, Kayhan Zrar, Kamalrulnizam, Abu Bakar

“…Simulation experiments were conducted to evaluate the performance of FLCCA in terms of the number of clusters formed, reaffiliation count and clustering control overheads. …”
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