Search Results - (( developing greedy method algorithm ) OR ( java simulation optimization algorithm ))

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  1. 1

    Routing problem in rectangular mesh network using Dijkstra’s based Greedy method by Noraziah, Adzhar, Shaharuddin, Salleh, Yuhani, Yusof, Muhammad Azrin, Ahmad

    Published 2018
    “…This paper presents a complete routing algorithm which can further refine the solution by using Dijkstra’s based greedy method. …”
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  2. 2

    Routing problem in rectangular mesh network using shortest path based Greedy method by Noraziah, Adzhar, Shaharuddin, Salleh, Yuhani, Yusof, Muhammad Azrin, Ahmad

    Published 2019
    “…This paper presents a complete routing algorithm which can further refine the solution by using Dijkstra's based greedy method. …”
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  3. 3

    Multi-base number representation in application to scalar multiplication and pairing computation by Mohammed Ismail, Abdelwahed

    Published 2011
    “…In this work, an extension of Greedy algorithm called xGreedy, is proposed. It finds the best approximated powers of each base to be used to convert large integers to new addition chains. …”
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  4. 4
  5. 5

    Routing problem in rectangular mesh network using shortest path based Greedy method by Noraziah, Adzhar, Shaharuddin, Salleh, Yuhani, Yusof, Muhammad Azrin, Ahmad

    Published 2019
    “…This paper presents a complete routing algorithm which can further refine the solution by using Dijkstra's based greedy method. …”
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    Conference or Workshop Item
  6. 6

    Information Theoretic-based Feature Selection for Machine Learning by Muhammad Aliyu, Sulaiman

    Published 2018
    “…Besides, this thesis developed a hybrid filter method to enhance the performance of the IFS. …”
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  7. 7

    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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  8. 8

    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
  9. 9

    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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  12. 12

    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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  13. 13
  14. 14

    Optimizing kindergarten schedule using : graph coloring / Nur Nabilah Salleh Muner by Salleh Muner, Nur Nabilah

    Published 2019
    “…The greedy algorithm was used to color the graph and it was supported by the C++ program. …”
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    Research Reports
  15. 15

    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
  16. 16

    Influence maximisation towards target users and minimal diffusion of information based on information needs by Temitope, Olanrewaju Abdus-Samad

    Published 2020
    “…IDTU was developed on greedy approach by using graph sketches to improve the selection of influencers that maximize influence spread to a set of target users. …”
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  17. 17

    Enhancement of Ant System Algorithm for Course Timetabling Problem by Djamarus, Djasli

    Published 2009
    “…This research starts with developing an algorithm based on original concept of Ant System Algorithm. …”
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  18. 18

    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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  19. 19

    Integration Of Travel Time Zone For Optimal Siting Of Emergency Facilities by Indriasari, Vini

    Published 2008
    “…Fire stations in Jakarta Selatan were chosen for simulation. Two algorithms, Greedy Adding (Add) and Greedy Adding with Travel Time Evaluation (GAT), were applied to solve the optimization problem of the MSAP. …”
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  20. 20

    Robust variable selection methods for large- scale data in the presence of multicollinearity, autocorrelated errors and outliers by Uraibi, Hassan S.

    Published 2016
    “…Hence, Robust-LARS (RLARS-RFCH) based on √ consistent multivariate (RFCH) correlation matrix is developed. The proposed method is computationally efficient and its performance outperformed the RLARS-Winsor The algorithm of all possible subsets is greedy and it is inefficient and unstable in the presence of autocorrelated errors and outliers. …”
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