Search Results - (( java loading optimization algorithm ) OR ( basic orientation learning algorithm ))

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  1. 1

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

    Published 2012
    “…This research proposes an enhancement of the ant colony optimization algorithm that caters for dynamic scheduling and load balancing in the grid computing system. …”
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    Monograph
  2. 2

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

    Published 2011
    “…This research proposes an Enhanced Ant Colony Optimization (EACO) algorithm that caters dynamic scheduling and load balancing in the grid computing system. …”
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    Thesis
  3. 3

    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
  4. 4

    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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  5. 5
  6. 6

    Adaptive security architecture for protecting RESTful web services in enterprise computing environment by Beer, M.I., Hassan, M.F.

    Published 2018
    “…The proposed security architecture is constructed as an adaptive way-forward Internet-of-Things (IoT) friendly security solution that is comprised of three cyclic parts: learn, predict and prevent. A novel security component named â��intelligent security engineâ�� is introduced which learns the possible occurrences of security threats on SOA using artificial neural networks learning algorithms, then it predicts the potential attacks on SOA based on obtained results by the developed theoretical security model, and the written algorithms as part of security solution prevent the SOA attacks. …”
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    Article
  7. 7

    Adaptive security architecture for protecting RESTful web services in enterprise computing environment by Beer, M.I., Hassan, M.F.

    Published 2018
    “…The proposed security architecture is constructed as an adaptive way-forward Internet-of-Things (IoT) friendly security solution that is comprised of three cyclic parts: learn, predict and prevent. A novel security component named â��intelligent security engineâ�� is introduced which learns the possible occurrences of security threats on SOA using artificial neural networks learning algorithms, then it predicts the potential attacks on SOA based on obtained results by the developed theoretical security model, and the written algorithms as part of security solution prevent the SOA attacks. …”
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    Article
  8. 8

    Computerized simulation system for ECM radar system by Salleh, Mohamad Sabri

    Published 2007
    “…The principle of electromagnetic spectrum is the basic background for all calculation and simulation. …”
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  9. 9

    Raspberry Pi-Based Finger Vein Recognition System Using PCANet by Quek, Ee Wen

    Published 2018
    “…For classification, k-Nearest Neighbours (kNN) with Euclidean distance algorithm is implemented. An enhancement version for kNN algorithm, k-General Nearest Neighbours (kGNN) have been proposed at initial stage. …”
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    Monograph
  10. 10

    Sensorless induction motor speed control for electric vehicles using enhanced hybrid flux estimator with ann-ifoc controller by Sepeeh, Muhamad Syazmie

    Published 2022
    “…The function of the ANN was to improve speed-tracking performance, and the learning rate of the ANN inside the indirect FOC’s structure trained using the Levenberg-Marquardt (LM) algorithm was varied in order to increase speed-tracking accuracy when combined with the improved ANN speed controller. …”
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    Thesis