Search Results - (( using optimization method algorithm ) OR ( data distribution center algorithm ))

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  1. 1

    Optimal configuration of wind farms in radial distribution system using particle swarm optimization technique by Kumar, M., Das, B., Nallagownden, P., Elamvazuthi, I., Khan, S.A.

    Published 2018
    “…The optimal location for these wind farms were pinpointed via particle swarm optimization (PSO) algorithm using standard IEEE 33 radial distribution system. …”
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    Article
  2. 2

    Optimal configuration of wind farms in radial distribution system using particle swarm optimization technique by Kumar, M., Das, B., Nallagownden, P., Elamvazuthi, I., Khan, S.A.

    Published 2018
    “…The optimal location for these wind farms were pinpointed via particle swarm optimization (PSO) algorithm using standard IEEE 33 radial distribution system. …”
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    Article
  3. 3

    Metaheuristic optimization techniques for localization in outdoor wireless sensor networks: a comprehensive review by Gumaida, Bassam, Ibrahim, Adamu Abubakar

    Published 2025
    “…This paper provides an overview of localization algorithms, including centralized and distributed algorithms. …”
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    Article
  4. 4

    Mathematical models and optimization algorithms for low-carbon Location-Inventory-Routing Problem with uncertainty by Liu, Lihua

    Published 2024
    “…This thesis also aims to solve the low-carbon LIRP model with uncertainty factors such as carbon trading, customer demand, shortages, and soft time windows using advanced algorithms. Three LIRP models involving multiple distribution centers and periods are proposed. …”
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    Thesis
  5. 5
  6. 6

    Personalized one-shot local adaptation federated learning for mortality prediction in multi-center Intensive Care Unit by Deng, Ting

    Published 2024
    “…Step 3 automatically evolves the best-fitting parameters for the highly personalized model at each center using an adapted genetic algorithm. Ultimately, this typical "FL training + local adaptation" PFL method can enhance model predictive accuracy by automatically generating a highly personalized model for each ICU center, guided by the FL sharing model. …”
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    Thesis
  7. 7

    Logistics center location-inventory-routing problem optimization: a systematic review using PRISMA method by Liu, Lihua, Lee, Lai Soon, Seow, Hsin Vonn, Chen, Chuei Yee

    Published 2022
    “…When dealing with the LIRP, heuristic and metaheuristic algorithms are the most widely used solution methodologies in the literature. …”
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    Article
  8. 8
  9. 9

    A New Swarm-Based Framework for Handwritten Authorship Identification in Forensic Document Analysis by Draman @ Muda, Azah Kamilah, Choo, Yun Huoy, Draman @ Muda, Noor Azilah

    Published 2014
    “…This chapter instead focuses on identifying the unique individual significant features of word shape by using feature selection method prior the identification task. …”
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    Book Chapter
  10. 10

    A new swarm-based framework for handwritten authorship identification in forensic document analysis by Pratama, Satrya Fajri, Draman @ Muda, Azah Kamilah, Choo, Yun Huoy, Draman @ Muda, Noor Azilah

    Published 2014
    “…This chapter instead focuses on identifying the unique individual significant features of word shape by using feature selection method prior the identification task. …”
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    Book Chapter
  11. 11

    Energy-efficient algorithms for dynamic virtual machine consolidation in cloud data centers by Khoshkholghi, Mohammad Ali, Derahman, Mohd Noor, Abdullah, Azizol, Subramaniam, Shamala, Othman, Mohamed

    Published 2017
    “…In this paper, several novel algorithms are proposed for the dynamic consolidation of VMs in cloud data centers. …”
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    Article
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    Performance evaluation of load balancing algorithm for virtual machine in data centre in cloud computing by Parmesivan, Yuganes, Hasan, Sazlinah, Muhammed, Abdullah

    Published 2018
    “…Cloud computing has become biggest buzz in the computer era these days.It runs entire operating systems on the cloud and doeverything on cloud to store data off-site.Cloud computing is primarily based on grid computing, but it’s a new computational model.Cloud computing has emerged into a new opportunity to further enhance way of hosting data centre and provide services.The primary substance of cloud computing is to deal the computing power,storage,different sort of stages and services which assigned tothe external users on demand through the internet.Task scheduling in cloud computing is vital role optimisation and effective dynamic resource allocation for load balancing.In cloud, the issue focused is under utilisation and over utilisation of the resources to distribute workload of multiple network links for example,when cloud clients try to access and send request tothe same cloud server while the other cloud server remain idle at that moment, leads to the unbalanced of workload on cloud data centers.Thus, load balancing is to assign tasks to the individual cloud data centers of the shared system so that no single cloud data centers is overloaded or under loaded.A Hybrid approach of Honey Bee (HB) and Particle Swarm Optimisation (PSO) load balancing algorithm is combined in order to get effective response time.The proposed hybrid algorithm has been experimented by using CloudSim simulator.The result shows that the hybrid load balancing algorithm improves the cloud system performance by reducing the response time compared to the Honey Bee (HB) and Particle Swarm Optimisation (PSO) load balancing algorithm.…”
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    Article
  14. 14

    A Center-Based Stable Evolving Clustering Algorithm With Grid Partitioning And Extended Mobility Features For VANETs by Talib, Mohammed Saad, Abdullah, Nihad Ibrahim, Hassan, Aslinda, Abal Abas, Zuraida, Mohammed Al-Khazraji, Ali Abdul-Jabbar, Alamery, Thamer, Ibrahim, Ali Jalil

    Published 2020
    “…An improvement percentage of the efficiency in (CEC-GP) over the benchmarks Center based stable clustering (CBSC) and evolving data clustering algorithm (EDCA) is 65% and 394% respectively.…”
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    Article
  15. 15

    Application of genetic algorithm methods to optimize flowshop sequencing problem by Mohd Fadil, Md Sairi

    Published 2008
    “…Genetic algorithm method was one of the methods that were widely used in solving optimization problem. …”
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    Undergraduates Project Papers
  16. 16

    Energy and performance efficient resource allocation for cloud-based data centers by Akhter, Nasrin

    Published 2015
    “…This thesis demonstrates that the dynamic consolidations of virtualmachines in cloud data centers by proposing energy efficient algorithms and policies. …”
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    Thesis
  17. 17

    Sizing optimization of large-scale grid connected photovoltaic system using dolphin echolocation algorithm / Muhammad Zakyizzuddin Rosselan by Rosselan, Muhammad Zakyizzuddin

    Published 2018
    “…Later, an Iterative-based Sizing Algorithm (ISA) was developed to determine the optimal sizing solution which was later used as benchmark for sizing algorithms using optimization methods. …”
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    Thesis
  18. 18

    An improved method using fuzzy system based on hybrid boahs for phishing attack detection by Noor Syahirah, Nordin

    Published 2022
    “…Moreover, Butterfly Optimization Algorithm and Harmony Search Algorithm were combined as optimization method led to a new method named BOAHS. …”
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    Thesis
  19. 19

    Wind farm reactive power optimization by using imperialist competitive algorithm by Soheilirad, Mohammadsoroush, Hizam, Hashim, Farzan, Payam, Hojabri, Mojgan, Fallah, Seyedeh Narjes, Soheilirad, G.

    Published 2013
    “…In this paper a new evolutionary computing method based on imperialist competitive algorithm (ICA) is used for optimization of the reactive power in a wind farm. …”
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    Conference or Workshop Item
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    SA-EVPS ALGORITHM FOR DISCRETE SIZE OPTIMIZATION OF THE 582-BAR SPATIAL TRUSS STRUCTURE by Paknahad, M., Hosseini, P., Hakim, S.J.S

    Published 2023
    “…Nowadays, approximate optimization methods are widely used. This study utilized the Self Adaptive Enhanced Vibrating Particle System (SA-EVPS) algorithm as an approximate optimization method, since the EVPS algorithm requires experimental parameters. …”
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    Article