Search Results - (( pattern reduction clustering algorithm ) OR ( java simulation optimization algorithm ))

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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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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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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Low area Programmable Memory Built-In Self-Test (PMBIST) for small embedded ram cores / Nur Qamarina Mohd Noor by Mohd Noor, Nur Qamarina

“…The first experiment is performed by clustering test patterns of RAMs under test. The second experiment deeply encodes the clusters of test patterns to improve the cluster technique to allow multiple test data types. …”
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Clustering of large time-series datasets using a multi-step approach / Saeed Reza Aghabozorgi Sahaf Yazdi by Yazdi, Saeed Reza Aghabozorgi Sahaf

“…Several studies which focus on time-series clustering have been conducted in said areas. Many of these studies focus on the time complexity of time-series clustering in large datasets and utilize dimensionality reduction approaches and conventional clustering algorithms to address the problem. …”
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An artificial neural network model for multi dimension reduction and data structure exploration, Proceedings of International Conference of Soft Computing and Pattern Recognition (... by Teh, Chee Siong, Ming Leong, Yii, Chen, Chwen Jen

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Pairwise clusters optimization and cluster most significant feature methods for anomaly-based network intrusion detection system (POC2MSF) / Gervais Hatungimana by Hatungimana, Gervais

“…Most of researches in IDS which use k-centroids-based clustering methods like K-means, K-medoids, Fuzzy, Hierarchical and agglomerative algorithms to baseline network traffic suffer from high false positive rate compared to signature-based IDS, simply because the nature of these algorithms risk to force some network traffic into wrong profiles depending on K number of clusters needed. …”
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Data-driven dynamic clustering framework for mitigating the adverse economic impact of Covid-19 lockdown practices by Rahman, Md. Arafatur, Nafees, Zaman, A. Taufiq, Asyhari, Al-Turjman, Fadi, Alam Bhuiyan, Md. Zakirul, Mohamad Fadli, Zolkipli

“…The findings signify the promises of dynamic clustering for lockdown coverage reduction, reduced economic loss, and military unit deployment reduction, as well as assess potential impact of uncooperative civilians on the contamination rate. …”
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OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT by Murad S.S., Badeel R., Alsandi N.S.A., Alshaaya R.F., Ahmed R.A., Muhammed A., Derahman M.

“…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. …”

Adaptive Feature Selection and Image Classification Using Manifold Learning Techniques by ASHRAF, AMNA, MOHD NAWI, NAZRI, MUHAMMAD AAMIR, MUHAMMAD AAMIR

“…In the first phase, the manifold learning approach is used to improve the ‘feature selection by clustering’. Clustering algorithms such as K-means, spectral clustering, and the Gaussian Mixer Model have been tested with manifold learning approaches for adaptive feature selection. …”
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A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition by Babiker, Elsadig Ahmed Mohamed

“…A vector quantization model that incorporate rough sets attribute reduction and rules generation with a modified version of the K-means clustering algorithm was developed, implemented and tested as a part of a speech recognition framework, in which the Learning Vector Quantization (LVQ) neural network model was used in the pattern matching stage. …”
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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

“…This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
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Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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Resource management in grid computing using ant colony optimization by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

“…Resources with high pheromone value are selected to process the submitted jobs.Global pheromone update is performed after completion 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 other ant based algorithm, in terms of resource utilization.Experimental results show that EACO produced better grid resource management solution.…”
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Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter by Azhar, Nur Huwaina

“…Cloudsim is used as Discrete Event Simulation tool and Java as coding language to evaluate LACE algorithm. …”
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Influence of shortest route approximation on relegating urban area’s transportation network priorities by Farid Morsidi, Haldi Budiman

“…This greedy pathfinding algorithm is regarded as proactive for application in several known neighboring routing characteristics, including customer clustering aspects in vehicle routing and location-allocation instances for optimal resource allocation.…”
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Local-based stereo matching algorithm using multi-cost pyramid fusion, hybrid random aggregation and hierarchical cluster-edge refinement by Kadmin, Ahmad Fauzan

“…Then, a new proposed cost aggregation based on the Hybrid Random Aggregation (HA) was implemented that utilized modified Iterative Non-Local Guided Filter (iNLGF), Simple Linear Iterative Clustering (SLIC), Graph Segmentation (GS) and Extended Restart Random Walk (eRWR) for error reduction. …”
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Filtering of Background DNA Sequences Improves DNA Motif Prediction Using Clustering Techniques by Lee, Nung Kion, Chieng, Allen Hoon Choong

“…Noisy objects have been known to affect negatively on the performance of clustering algorithms. This paper addresses the problem of high false positive rates in using self-organizing map (SOM) for DNA motif prediction due to the noisy background sequences in the input dataset. …”
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SG-PBFS : Shortest Gap-Priority Based Fair Scheduling technique for job scheduling in cloud environment by Murad, Saydul Akbar, Zafril Rizal, M. Azmi, Muzahid, Abu Jafar Md, Bhuiyan, Md Khairul Bashar, Saib, Md, Rahimi, Nick, Prottasha, Nusrat Jahan, Bairagi, Anupam Kumar

“…To conduct this experiment, we employed the CloudSim simulator, which is implemented using the Java programming language.…”
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A new model for iris data set classification based on linear support vector machine parameter's optimization by Faiz Hussain, Zahraa, Ibraheem, Hind Raad, Alsajri, Mohammad, Ali, Ahmed Hussein, Mohd Arfian, Ismail, Shahreen, Kasim, Sutikno, Tole

“…In this study, we proposed a newly mode for classifying iris data set using SVM classifier and genetic algorithm to optimize c and gamma parameters of linear SVM, in addition principle components analysis (PCA) algorithm was use for features reduction.…”
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