Search Results - (( simulation evaluation based algorithm ) OR ( evolution optimization based algorithm ))

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  1. 1

    Cloudlet deployment and task offloading in mobile edge computing using variable-length whale and differential evolution optimization and analytical hierarchical process for decisio... by Daba, Layth Muwafaq Abdulhussein

    Published 2023
    “…Comparing this developed algorithm with other algorithms shows its superiority in multi-objective optimization (MOO) evaluation metrics. …”
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    Thesis
  2. 2

    PMT : opposition based learning technique for enhancing metaheuristic algorithms performance by Hammoudeh, S. Alamri

    Published 2020
    “…To evaluate the PMT’s performance and adaptability, the PMT was applied to four contemporary metaheuristic algorithms, Differential Evolution, Particle Swarm Optimization, Simulated Annealing, and Whale Optimization Algorithm, to solve 15 well-known benchmark functions as well as 2 real world problems based on the welded beam design and pressure vessel design. …”
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    Thesis
  3. 3

    Evolution of RF-signal cognition for wheeled mobile robots using pareto multi-objective optimization by Chin, Kim On, Teo, Jason Tze Wi

    Published 2009
    “…The generated controllers are evaluated on its performances based on Pareto analysis. …”
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    Article
  4. 4

    Handover procedure between macrocell and femtocell in Long Term Evolution (LTE) network: article / Nurul Afzan Zakaria by Zakaria, Nurul Afzan

    Published 2013
    “…This proposed algorithm was developed and simulated to evaluate the performance of handover procedure in order to minimize an unnecessary handover, enhance the system capacity and improve the user's QoS level in the femtocell networks. …”
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    Article
  5. 5

    Handover procedure between macrocell and femtocell in long term evolution (LTE) network / Nurul Afzan Zakaria by Zakaria, Nurul Afzan

    Published 2013
    “…This proposed algorithm was developed and simulated to evaluate the performance of handover procedure in order to minimize an unnecessary handover, enhance the system capacity and improve the user's QoS level in the femtocell networks. …”
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    Thesis
  6. 6

    Optimized routing algorithm for mobile multicast source in Wireless Mesh Networks by Sanni, Mistura Laide, Hassan Abdalla Hashim, Aisha, Hassan, Wan Haslina, Anwar, Farhat, Ahmed, Gharib Subhi Mahmoud

    Published 2015
    “…Thus this paper proposes a Differential Evolution based optimized mobile multicast routing algorithm for the shared tree architecture. …”
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    Proceeding Paper
  7. 7

    Efficient radio resource management algorithms for downlink long term evolution networks by Mamman, Maharazu

    Published 2018
    “…The algorithm is based on the idea of the optimization problem in which resource allocation problem is formulated as an optimization problem. …”
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  8. 8

    An enhanced metaheuristic approach to solve quadratic assignment problem using hybrid technique by Hameed, Asaad Shakir

    Published 2021
    “…The valuate of performance HDDETS algorithm comparison to existing hybrid-based algorithms, namely: Biogeography-Based Optimization Tabu Search (BBOTS), Whale Algorithm with Tabu Search (WAITS), Hybrid Ant System (HAS), Lexisearch and Genetic Algorithms (LSGA), and Golden Ball Simulated Annealing (GBSA) algorithms. …”
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    Thesis
  9. 9

    PMT: opposition-based learning technique for enhancing meta-heuristic performance by Alamri, Hammoudeh S., Kamal Z., Zamli

    Published 2019
    “…To evaluate the PMT's performance and adaptability, the PMT has been applied to four contemporary meta-heuristic algorithms, differential evolution (DE), particle swarm optimization (PSO), simulated annealing (SA), and whale optimization algorithm (WOA), to solve 15 well-known benchmark functions. …”
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    Article
  10. 10

    Cluster head selection optimization in wireless sensor network via genetic-based evolutionary algorithm by Vincent Chung, Hamzarul Alif Hamzah, Norah Tuah, Kit, Guan Lim, Min, Keng Tan, Kenneth Tze Kin Teo

    Published 2020
    “…Genetic-based evolutionary algorithms such as Genetic Algorithm (GA) and Differential Evolution (DE) have been popularly used to optimize cluster head selection in WSN to improve energy efficiency for the extension of network lifetime. …”
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    Article
  11. 11

    Reliability assessment of power generation systems using intelligent search based on disparity theory by Kadhem, Athraa Ali, Abdul Wahab, Noor Izzri, Aris, Ishak, Jasni, Jasronita, Abdalla, Ahmed N.

    Published 2017
    “…In this paper, a novel optimization technique named the disparity evolution genetic algorithm (DEGA) is proposed for reliability assessment of power generation. …”
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    Article
  12. 12

    Quality of service and energy efficient aware (QEEA) scheduling algorithm for long term evolution (LTE) network / Nurulanis Mohd Yusoff by Mohd Yusoff, Nurulanis

    Published 2017
    “…The simulation process was conducted using Network Simulator-3 (NS-3) and the performance of these packet scheduling algorithms were evaluated based on the performance metrics of throughput, delay, packet loss ratio (PLR), energy consumption rate (ECR), and EE for the voice over IP (VoIP), video and File Transfer Protocol (FTP) applications. …”
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    Thesis
  13. 13

    Reliability Assessment of Power Generation Systems Using Intelligent Search Based on Disparity Theory by Kadhem, Athraa Ali, Noor Izzri, Abdul Wahab, Ishak, Aris, Jasronita, Jasni, Abdalla, Ahmed N.

    Published 2017
    “…In this paper, a novel optimization technique named the disparity evolution genetic algorithm (DEGA) is proposed for reliability assessment of power generation. …”
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    Article
  14. 14

    Self-configured link adaptation using channel quality indicator-modulation and coding scheme mapping with partial feedback for green long-term evolution cellular systems by Salman, Mustafa Ismael

    Published 2015
    “…To achieve this objective, an iterative approach based on swarm intelligence is used to find the optimal CQI threshold at which the competing criteria are optimized. …”
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    Thesis
  15. 15

    Quality of service and scheduling performance optimization in LTE networks / Abubakar Auwal Idris by Abubakar Auwal , Idris

    Published 2017
    “…The developed algorithm is simulated in LTE-Sim simulator released 5 in terms of three QoS metrics (1) Packet Loss Ratio (2) Delay (3) Throughput. …”
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    Thesis
  16. 16

    Energy and spectral efficiency balancing algorithm for energy saving in LTE downlinks by Maharazu, Mamman, Mohd Hanapi, Zurina, Mahmoud Alrashah, Mohamed Alhadi

    Published 2021
    “…In contrast with existing works, this study proposes an efficient SE and EE trade-off algorithm for saving energy in downlink Long Term Evolution (LTE) networks to concurrently optimize SE and EE while considering battery life at the Base Station (BS). …”
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    Article
  17. 17
  18. 18

    Using the evolutionary mating algorithm for optimizing deep learning parameters for battery state of charge estimation of electric vehicle by Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Nor Farizan, Zakaria, Mohd Mawardi, Saari

    Published 2023
    “…According to the simulation results, the proposed EMA-DL algorithm was found to outperform all the other compared algorithms based on the evaluated metrics. …”
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    Article
  19. 19

    Exp-bet packet scheduling algorithm for multiple traffic services in long term evolution (LTE) system / Ku Siti Syahidah Ku Mohd Noh by Ku Mohd Noh, Ku Siti Syahidah

    Published 2016
    “…The simulation process has been done using the LTE-Sim simulator and the performance of these packet scheduling algorithms were evaluated based on the performance metric of fairness index, throughput, packet loss rate and delay for VoIP, video and best effort flows. …”
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    Thesis
  20. 20

    Optimal placement of unified power flow controller by dynamic implementation of system-variable-based voltage-stability indices to enhance voltage stability by Ahmad, S., Albatsh, F.M., Mekhilef, Saad, Mokhlis, Hazlie

    Published 2016
    “…Furthermore, to verify the suitability of the explored locations, a comparative study has been conducted after placing UPFC in the present locations and other locations obtained using optimization techniques like particle swarm optimization (PSO), differential evolution (DE), genetic algorithm (GA), and bacteria foraging algorithm (BFA). …”
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    Article