Search Results - (( data collaborative learning algorithm ) OR ( java simulation optimization algorithm ))

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

    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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    Thesis
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    Ant colony optimization algorithm for load balancing in grid computing by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

    Published 2012
    “…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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    Monograph
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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.

    Published 2023
    “…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. …”
    Review
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    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

    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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    Thesis
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    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    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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    Thesis
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    Deep reinforcement learning approaches for multi-objective problem in Recommender Systems by Ee, Yeo Keat

    Published 2022
    “…Besides that, the experiment shows that agent which learning sequential data has earned lower precision by 17.57% and novelty by 4.68% compared to the agent that without learning sequential data, however, it achieved better diversity by 2.66%. …”
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    Thesis
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    Resource management in grid computing using ant colony optimization by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

    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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    Monograph
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    A machine learning approach to tourism recommendations system by Chia, An

    Published 2025
    “…Scalability problems arise when the system struggles to handle large volumes of data or a growing number of users and items. To overcome this problem, this project implements machine learning algorithms with collaborative filtering, content-based filtering and hybrid filtering approaches. …”
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    Final Year Project / Dissertation / Thesis
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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

    Published 2019
    “…Cloudsim is used as Discrete Event Simulation tool and Java as coding language to evaluate LACE algorithm. …”
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    Thesis
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    Temporal integration based factorization to improve prediction accuracy of collaborative filtering by Al-Qasem, Al-Hadi Ismail Ahmed

    Published 2016
    “…The rating matrix typically contains a high percentage of unknown rating scores which is called the data sparsity problem. The data sparsity problem has been solved by several approaches such as Bayesian probabilistic, machine learning, genetic algorithm, particle swarm optimization and matrix factorization. …”
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    Thesis
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    A collaborative filtering approach using machine learning and business intelligence: a critical review by Muhamad Ibrahim, Najhan, Abiduzzaman, S M, Abdul Raziff, Abdul Rafiez, Shah, Asadullah

    Published 2025
    “…Specifically, we discovered that combining deep learning techniques with reinforcement learning algorithms enhanced recommendation reliability by 35% while improving user engagement measures by 25%. …”
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    Article
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    Artificial Intelligence (AI) in the art and design industry / Fahmi Samsudin by Samsudin, Fahmi

    Published 2023
    “…It encompasses different types, such as rule-based AI using if-then statements for decision-making, machine learning which employs algorithms to analyze and learn from data, and deep learning utilizing artificial neural networks to learn from extensive datasets. …”
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    Article
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    Improved rsync algorithm to minimize communication cost using multi-agent systems for synchronization in multi-learning management systems by Mwinyi, Amir Kombo

    Published 2017
    “…This model enhances the interoperability and collaboration of HLIs in terms of synchronization and sharing of learning contents. …”
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    Thesis
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    A Denoising Generative Adversarial Network Based On Enhanced Feature Mapping Of Data Augmentation For Image Synthesis by Chen, Li

    Published 2024
    “…Specifically, the generator's ability is enhanced by adding data with noise as an extra input. This requires the generator to learn how to generate images from partially damaged data, leading to better representations learned from the data. …”
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    Thesis
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    Contextualising Computational Thinking: A Case Study in Remote Rural Sarawak Borneo by Nur Hasheena, Anuar, Fitri Suraya, Mohamad, Jacey Lynn, Minoi

    Published 2020
    “…The study used observational field notes, comprehension checks, and participants’ learning products as primary data sources. Findings showed that indigenous children’s learning characteristics were primarily ‘learning-by-making’, collaborative, highly motivated, playful, curious, and imaginative while they attempted to learn Computational thinking. …”
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    Article
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