Search Results - (( wolf optimization strategy algorithm ) OR ( evolution optimization method algorithm ))

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  1. 1

    Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain by Mohamad Zihin , Mohd Zain

    Published 2018
    “…The proposed method is tested on 10 multi-objective benchmark problems of CEC 2009 and compared with four metaheuristics: Multi-Objective Grey Wolf Optimizer (MOGWO), Multi-Objective Evolutionary Algorithm Based on Decomposition (MOEA/D), Multi-Objective Differential Evolution (MODE) and MOPSO. …”
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    Thesis
  2. 2

    A New Co-Evolution Binary Particle Swarm Optimization With Multiple Inertia Weight Strategy For Feature Selection by Too, Jing Wei, Abdullah, Abdul Rahim, Mohd Saad, Norhashimah

    Published 2019
    “…To examine the effectiveness of proposed method, four recent and popular feature selection methods namely BPSO, genetic algorithm (GA), binary gravitational search algorithm (BGSA) and competitive binary grey wolf optimizer (CBGWO) are used in a performance comparison. …”
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    Article
  3. 3

    Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals by Too, Jing Wei

    Published 2020
    “…The fourth method is Competitive Binary Grey Wolf Optimizer (CBGWO), which is an improved version of BGWO by utilizing the competition and leader enhancement strategies. …”
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    Thesis
  4. 4

    Urban connected vehicle lane planning based on improved Frank Wolfe algorithm by Anqi, Jiang, Faziawati, Abdul Aziz, Norsidah, Ujang, Mohd Afzan, Mohamed

    Published 2025
    “…The results showed that the accuracy and recall of the proposed improved whale optimization algorithm on the Iris dataset were 95.27% and 92.65%, respectively, which were superior to traditional whale optimization algorithm, moth flame optimization algorithm, moth flame optimization algorithm combined with chaos strategy, and adaptive firefly optimization algorithm. …”
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    Article
  5. 5

    Algorithmic Loan Risk Prediction Method Based on PSO-EBGWO-Catboost by Chen, Suihai, Bong, Chih How, Chiu, Po Chan

    Published 2024
    “…Under the background of big data, it is of practical significance to prevent loan risk by the machine learning algorithm. Aiming at the characteristics of unbalanced loan data and high noise, this paper proposes an improved Gray Wolf optimization strategy (PSOEBGWO). …”
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    Article
  6. 6

    An ensemble of neural network and modified grey wolf optimizer for stock prediction by Das, Debashish

    Published 2019
    “…Grey Wolf Optimizer (GWO) is a recently developed meta-heuristic algorithm which is appealing to researcher owing to its demonstrated performance as cited in the scientific literature. …”
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    Thesis
  7. 7

    Grey wolf optimization for enhanced performance in wind power system with dual-star induction generators by Benamara K., Amimeur H., Hamoudi Y., Abdolrasol M.G.M., Cali U., Ustun T.S.

    Published 2025
    “…The primary objective is to optimize the entire system by fine-tuning PID and PI controllers through the application of meta-heuristic algorithms, specifically Grey Wolf Optimization (GWO) and Particle Swarm Optimization (PSO). …”
    Article
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    Development of an improved GWO algorithm for solving optimal paths in complex vertical farms with multi-robot multi-tasking by Shen, Jiazheng, Hong, Tang Sai, Fan, Luxin, Zhao, Ruixin, Mohd Ariffin, Mohd Khairol Anuar, As’arry, Azizan

    Published 2024
    “…The EPDE-GWO algorithm is compared with Genetic Algorithm (GA), Simulated Annealing (SA), Dung Beetle Optimizer (DBO), and Particle Swarm Optimization (PSO). …”
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    Article
  11. 11

    Optimal sizing of autonomous hybrid microgrids with economic analysis using grey wolf optimizer technique by Tukkee, Ahmed Sahib, Abdul Wahab, Noor Izzri, Mailah, Nashiren Farzilah

    Published 2023
    “…Different configurations of hybrid Microgrids are proposed comprising various generating re�sources to meet the electrical load of small villages in Malaysia. Grey Wolf Optimizer (GWO) is employed to minimize the cost of energy COE (/kWh) considering operation constraints. …”
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    Article
  12. 12

    CSGO: a game-inspired metaheuristic algorithm for global optimization by Rahman, Tuan A. Z., Md Rezali, Khairil Anas, As'arry, Azizan

    Published 2023
    “…This paper presents a video game-inspired meta-heuristic algorithm and its performance evaluation. This optimizer algorithm is developed by assembling impressive features of previous well-known optimizer algorithms such as stochastic fractal search (SFS), artificial gorilla troops optimizer (GTO) and marine predators algorithm (MPA) with addition of chaotic operators. …”
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    Conference or Workshop Item
  13. 13

    Optimization and Control of Economic Dispatch for Power Systems by Ab Ghani, Mohd Ruddin

    Published 1993
    “…The formulation caters for loading and deloading rates, limits on generators outputs, spinning reserve requirements and group power import-export limits. The modelling strategy and solution techniques employed are based on Dantzig-Wolfe Decomposition principle, which produces a master problem solved by revised simplex method and a capacitated transshipment subproblem solved by network flow algorithm. …”
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  14. 14

    Optimal power flow with renewable power generations using hyper-heuristic technique by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

    Published 2024
    “…The technique selects and integrates the strengths of three low-level meta-heuristics algorithms, including Grey Wolf Optimizer (GWO), Barnacles Mating Optimizer (BMO), and Whale Optimization Algorithm (WOA), to achieve the best possible results. …”
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    Book Chapter
  15. 15

    Parameter Estimation Using Improved Differential Evolution And Bacterial Foraging Algorithms To Model Tyrosine Production In Mus Musculus(Mouse) by Jia, Xing Yeoh, Chuii, Khim Chong, Mohd Saberi, Mohamad, Yee, Wen Choon, Lian, En Chai, Safaai, Deris, Zuwairie, Ibrahim

    Published 2015
    “…The hybrid of Differential Evolution algorithm with Kalman Filtering and Bacterial Foraging algorithm is a novel global optimisation method implemented to obtain the best kinetic parameter value. …”
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    Article
  16. 16

    A new modified differential evolution algorithm scheme-based linear frequency modulation radar signal de-noising by Al-Dabbagh, Mohanad Dawood, Al-Dabbagh, Rawaa Dawoud, Raja Abdullah, Raja Syamsul Azmir, Hashim, Fazirulhisyam

    Published 2015
    “…The main intention of this study was to investigate the development of a new optimization technique based on the differential evolution (DE) algorithm, for the purpose of linear frequency modulation radar signal de-noising. …”
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    Article
  17. 17

    A performance of AFIRO among asynchronous iteration strategy metaheuristic algorithms by Ab Rahman, Tasiransurini, Nor Azlina, Ab. Aziz, Zuwairie, Ibrahim

    Published 2023
    “…In the original paper, AFIRO was compared with the Particle Swarm Optimisation algorithm, Genetic Algorithm, and Grey Wolf Optimizer. …”
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    Article
  18. 18

    Adaptive Switching Gravitational Search Algorithm: An Attempt To Improve Diversity Of Gravitational Search Algorithm Through Its Iteration Strategy by Nor Azlina, Ab. Aziz, Zuwairie, Ibrahim, Marizan, Mubin, Shahdan, Sudin

    Published 2017
    “…The proposed ASw-GSA is also compared to original GSA, particle swarm optimization (PSO), genetic algorithm (GA), bat-inspired algorithm (BA) and grey wolf optimizer (GWO). …”
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    Article
  19. 19

    Differential evolution optimization algorithm based on generation systems reliability assessment integrated with wind energy by Kadhem, Athraa Ali, Abdul Wahab, Noor Izzri, Abdalla, Ahmed N.

    Published 2019
    “…This stuffy proposed a novel optimization method labeled the "Differential Evolution Optimization Algorithm" (DEOA) to assess the reliability of power generation systems (PGS). …”
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    Multiobjective optimization of bioethanol production via hydrolysis using hopfield- enhanced differential evolution by Ganesan, T., Elamvazuthi, I., Shaari, K.Z.K., Vasant, P.

    Published 2014
    “…In this chapter, the weighted sum scalarization approach is used in conjunction with three meta-heuristic algorithms: Differential Evolution (DE), Hopfield-Enhanced Differential Evolution (HEDE), and Gravitational Search Algorithm (GSA). …”
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    Book