Search Results - (( java simulation optimization algorithm ) OR ( self learning techniques algorithm ))
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…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
Published 2011“…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
Published 2012“…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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Development of web based learning content of animation algorithm on searching and sorting techniques / Nur Linda Abdi Nur
Published 2007“…The objectives of this project is to develop self-learning environment in learning searching and sorting algorithm, enhance understanding of student in learning searching and sorting technique and to apply web-based learning in computer science subject, which focus on courses that use searching and sorting algorithm.…”
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Advancements and challenges in mobile robot navigation: a comprehensive review of algorithms and potential for self-learning approaches
Published 2024“…In this review paper, a comprehensive review of mobile robot navigation algorithms has been conducted. The findings suggest that, even though the self-learning algorithms require huge amounts of training data and have the possibility of learning erroneous behavior, they possess huge potential to overcome challenges rarely addressed by the other traditional algorithms. …”
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OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT
Published 2023“…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. …”
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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…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
Published 2016“…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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An improved self organizing map using jaccard new measure for textual bugs data clustering
Published 2018“…Considering the unsupervised learning algorithms, Self-Organizing Map (SOM) considers the equally compatible algorithm for clustering, as both algorithms are closely related but different in way they were used in data mining. …”
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An improved self organizing map using jaccard new measure for textual bugs data clustering
Published 2018“…Considering the unsupervised learning algorithms, SelfOrganizing Map (SOM) considers the equally compatible algorithm for clustering, as both algorithms are closely related but different in way they were used in data mining. …”
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Resource management in grid computing using ant colony optimization
Published 2011“…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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An improved pheromone-based kohonen self-organising map in clustering and visualising balanced and imbalanced datasets
Published 2021“…However, similar to other clustering algorithms, this algorithm requires sufficient data for its unsupervised learning process. …”
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Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter
Published 2019“…Cloudsim is used as Discrete Event Simulation tool and Java as coding language to evaluate LACE algorithm. …”
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Development and usage of self-organising maps in high energy physics analysis with high performance computing / Mohd Adli Md Ali
Published 2017“…The Self-Organizing Map (SOM) was put forward by Teuvo Kohonen in 1982 as a computational technique to produce a set of globally ordered quantized vectors. …”
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An Improved Pheromone-Based Kohonen Self- Organising Map in Clustering and Visualising Balanced and Imbalanced Datasets
Published 2021“…However, similar to other clustering algorithms, this algorithm requires sufficient data for its unsupervised learning process. …”
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Intent-IQ: customer’s reviews intent recognition using random forest algorithm
Published 2025“…Data annotation using semi-supervised learning which is self-training technique need to be accomplished as the dataset is unlabeled. …”
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Survival versus non-survival prediction after acute coronary syndrome in Malaysian population using machine learning technique / Nanyonga Aziida
Published 2019“…The best performing model was compared with TIMI using an additional dataset that resulted in the ML model outperforming TIMI score (AUC 0.75 vs 0.60). Machine learning techniques for prediction and visualization of mortality related to ACS is presented in this study. …”
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Triangulating the implementation of hierarchical agglomerative clustering on MAR-learning usability data
Published 2023Conference Paper -
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An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA
Published 2025“…Using the NSL-KDD dataset for evaluation, the proposed method demonstrates superior performance compared to conventional algorithms and related deep learning techniques, achieving higher precision, recall, F1 scores and overall accuracy in both binary and multi-class classification tasks. …”
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