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  1. 1

    Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study by Li Yu Yab, Li Yu Yab, Wahid, Noorhaniza, A Hamid, Rahayu

    Published 2023
    “…—Whale Optimization Algorithm (WOA) and Grey Wolf Optimizer (GWO) are well-perform metaheuristic algorithms used by various researchers in solving feature selection problems. …”
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    Article
  2. 2

    Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study by Li Yu Yab, Li Yu Yab, Wahid, Noorhaniza, A Hamid, Rahayu

    Published 2023
    “…Whale Optimization Algorithm (WOA) and Grey Wolf Optimizer (GWO) are well-perform metaheuristic algorithms used by various researchers in solving feature selection problems. …”
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    Article
  3. 3

    Optimizing decentralized exam timetabling with a discrete whale optimization algorithm by Emily Sing Kiang Siew, San nah sze, Say leng goh

    Published 2025
    “…—In recent years, there has been increasing interest in intelligent optimization algorithms, such as the Whale Optimization Algorithm (WOA). …”
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    Article
  4. 4

    Optimizing Decentralized Exam Timetabling with a Discrete Whale Optimization Algorithm by Emily Siew, Sing Kiang, Sze, San Nah, Goh, Say Leng

    Published 2025
    “…In recent years, there has been increasing interest in intelligent optimization algorithms, such as the Whale Optimization Algorithm (WOA). …”
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    Article
  5. 5

    The influence of sentiments in digital currency prediction using hybrid sentiment-based Support Vector Machine with Whale Optimization Algorithm (SVMWOA) by Hitam, Nor Azizah, Ismail, Amelia Ritahani, Samsudin, Ruhaidah, Ameerbakhsh, Omair

    Published 2021
    “…The proposed Hybrid Sentiment-based Support Vector Machine with a Whale Optimization Algorithm (SVMWOA). will be evaluated and compared based on performance measures. …”
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    Proceeding Paper
  6. 6

    Improving amphetamine-type stimulants drug classification using chaotic-based time-varying binary whale optimization algorithm by Draman @ Muda, Azah Kamilah, Mohd Yusof, Norfadzlia, Pratama, Satrya Fajri, Carbo-Dorca, Ramon, Abraham, Ajith

    Published 2022
    “…Specific high-dimensional molecular descriptors of ATS and non-ATS drugs were employed to evaluate the efficiency of the proposed algorithm. …”
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    Article
  7. 7

    Voting algorithms for large scale fault-tolerant systems by Karimi, Abbas

    Published 2011
    “…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. …”
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    Thesis
  8. 8

    Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures by Koohi, Sina Zangbari

    Published 2020
    “…Any optimization algorithm is suitable for only a specific domain of optimization problems. …”
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    Thesis
  9. 9

    Variable Neighborhood Descent and Whale Optimization Algorithm for Examination Timetabling Problems at Universiti Malaysia Sarawak by Emily Sing Kiang, Siew

    Published 2025
    “…A constructive algorithm was developed to generate an initial feasible solution, which was subsequently refined using two primary approaches to evaluate their efficiency: Iterative Threshold Pipe Variable Neighborhood Descent (IT-PVND), and a modified Whale Optimization Algorithm (WOA). …”
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    Thesis
  10. 10

    Probabilistic ensemble fuzzy ARTMAP optimization using hierarchical parallel genetic algorithms by Loo, C.K., Liew, W.S., Seera, M., Lim, Einly

    Published 2015
    “…This was achieved by mitigating convergence in the genetic algorithms by employing a hierarchical parallel architecture. …”
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    Article
  11. 11

    Hybrid binary whale with harris hawks for feature selection by Alwajih, R., Abdulkadir, S.J., Al Hussian, H., Aziz, N., Al-Tashi, Q., Mirjalili, S., Alqushaibi, A.

    Published 2022
    “…As a result, feature selection is offered as a method for eliminating unwanted characteristics. This study introduces the BWOAHHO memetic technique, which combines the binary hybrid Whale Optimization Algorithm (WOA) with Harris Hawks Optimization (HHO). …”
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    Article
  12. 12

    Investigation on the dynamic of computation of semi autonomous evolutionary computation for syntactic optimization of a set of programming codes by Mohammad Sigit Arifianto, Tze, Kenneth Kin Teo, Liau, Chung Fan, Liawas Barukang, Zaturrawiah Ali Omar

    Published 2007
    “…Genetic Algorithm as one of the Evolutionary Computation method improve the execution of parallel programming codes by optimizing the number of processors and the distribution of data. …”
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    Research Report
  13. 13

    Improved black-winged kite algorithm and finite element analysis for robot parallel gripper design by Haohao, Ma, As’arry, Azizan, Yanwei, Feng, Lulu, Cheng, Delgoshaei, Aidin, Ismail, Mohd Idris Shah, Ramli, Hafiz Rashidi

    Published 2024
    “…This paper presents a comprehensive study on the design optimization of a robotic gripper, focusing on both the gripper modeling and the optimization of its parallel mechanism structure. …”
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    Article
  14. 14

    Sequential and parallel multiple tabu search algorithm for multiobjective urban transit scheduling problems by Uvaraja, Vikneswary

    Published 2018
    “…Additionally, the MTS algorithm is also implemented in parallel computing to produce parallel MTS for generating comparable solutions in shorter computational times. …”
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    Thesis
  15. 15

    Analysis of evolutionary computing performance via mapreduce parallel processing architecture / Ahmad Firdaus Ahmad Fadzil by Ahmad, Ahmad Firdaus

    Published 2014
    “…Examples of EC such as Genetic Algorithm (GA) and PSO (Particle Swarm Optimization) are prevalent due to their efficiency and effectiveness. …”
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    Thesis
  16. 16

    Distributed parallel deep learning with a hybrid backpropagation-particle swarm optimization for community detection in large complex networks by Shing, Chiang Ta, Mohammed Al-Andoli, Mohammed Nasser, Wooi, Ping Cheah

    Published 2022
    “…Next, the method is integrated with two optimization algorithms: (1) backpropagation (BP), which optimizes deep learning locally within each local chunk of the CN; (2) particle swarm optimization (PSO), which is used to improve the BP optimization involving all CN chunks. …”
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    Article
  17. 17

    PID Parameters Improvement for AGC in Three Parallel-Connected Power Systems by Mushtaq, Najeeb, Ramdan, Razali, K. G., Mohammed, Hamdan, Daniyal, Ali, M. Humada

    Published 2016
    “…The AGC loop is used to minimize the frequency deviation and control the power exchange in order to maintain them at their scheduled values due to the changes of the step-load disturbance. The optimal parameters of the PID scheme optimized by the proposed MS algorithm are compared with that one’s obtained by GA algorithm, and the proposed method has proven that its performance is more efficient and improved as well. …”
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    Conference or Workshop Item
  18. 18

    Design and analysis of high performance matrix filling for DNA sequence alignment accelerator using asic design flow: article / Nurzaima Mahmod by Mahmod, Nurzaima

    “…The scope of this paper is to optimize the DNA sequences alignment on the matrix rilling module by implementing a parallel method of the Smith-Waterman algorithm. …”
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    Article
  19. 19

    Design and analysis of high performance matrix filling for DNA sequence alignment accelerator using ASIC design flow / Nurzaima Mahmod by Mahmod, Nurzaima

    Published 2010
    “…The scope of this paper is to optimize the DNA sequences alignment on the matrix filling module by implementing a parallel method of the SmithWaterman algorithm. …”
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    Thesis
  20. 20

    Application Of Genetic Algorithms For Robust Parameter Optimization by Belavendram, N.

    Published 2010
    “…Genetic algorithms (GA) are fairly recent in this respect but afford a novel method of parameter optimization. …”
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    Article