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Showing 1 - 13 results of 13 for search 'nature-inspired optimization algorithm*', query time: 0.08s Refine Results
  1. 1
    Recent Advances of Chimp Optimization Algorithm: Variants and Applications

    Recent Advances of Chimp Optimization Algorithm: Variants and Applications by Daoud, Mohammad Sh.

    Published 2023
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  2. 2
    Improved Dwarf Mongoose Optimization for Constrained Engineering Design Problems

    Improved Dwarf Mongoose Optimization for Constrained Engineering Design Problems by Agushaka, Jeffrey O.

    Published 2022
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  3. 3
    On the Optimization of Band Gaps in Periodic Waveguides

    On the Optimization of Band Gaps in Periodic Waveguides by Jamil Renno (14070771)

    Published 2025
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  4. 4
    Performance assessment and exhaustive listing of 500+ nature-inspired metaheuristic algorithms

    Performance assessment and exhaustive listing of 500+ nature-inspired metaheuristic algorithms by Zhongqiang Ma (13765801)

    Published 2023
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  5. 5
    Whale optimization algorithm: analysis and full survey

    Whale optimization algorithm: analysis and full survey by Abualigah, Laith

    Published 2024
    “…The whale optimization algorithm (WOA) is a metaheuristic algorithm inspired by the hunting behavior of humpback whales. …”
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  6. 6
    Squirrel Search Algorithm for Portfolio Optimization

    Squirrel Search Algorithm for Portfolio Optimization by Dhaini, Mahdi

    Published 2019
    “…However, the successes of nature-inspired algorithms in hard computational optimization problems have encouraged researchers to design and apply these algorithms for a variety of optimization problems. …”
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  7. 7
    A Multiswarm Intelligence Algorithm for Expensive Bound Constrained Optimization Problems

    A Multiswarm Intelligence Algorithm for Expensive Bound Constrained Optimization Problems by Wali Khan Mashwani (14590504)

    Published 2021
    “…The suggested algorithm integrates the SI-based algorithms to evolve population and handle exploration versus exploitation issues. …”
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  8. 8
    Elk herd optimizer

    Elk herd optimizer by Al-Betar, Mohammed Azmi

    Published 2024
    “…This paper proposes a novel nature-inspired swarm-based optimization algorithm called elk herd optimizer (EHO). …”
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  9. 9
    Stochastic optimal power flow framework with incorporation of wind turbines and solar PVs using improved liver cancer algorithm

    Stochastic optimal power flow framework with incorporation of wind turbines and solar PVs using improved liver cancer algorithm by Noor Habib Khan (22224775)

    Published 2024
    “…<p dir="ltr">The present study introduces a nature inspired improved liver cancer algorithm (ILCA) for solving the non‐convex engineering optimization issues. …”
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  10. 10
    Coronavirus herd immunity optimizer (CHIO)

    Coronavirus herd immunity optimizer (CHIO) by Abou Doush, Iyad

    Published 2020
    “…In this paper, a new nature-inspired human-based optimization algorithm is proposed which is called coronavirus herd immunity optimizer (CHIO). …”
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  11. 11
    A Review on Swarm Intelligence and Evolutionary Algorithms for Solving the Traffic Signal Control Problem

    A Review on Swarm Intelligence and Evolutionary Algorithms for Solving the Traffic Signal Control Problem by Shaikh, Palwasha

    Published 2020
    “…Nature-inspired algorithms including evolutionary and swarm intelligence algorithms are gaining a lot of momentum. …”
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  12. 12
    Improved Reptile Search Algorithm by Salp Swarm Algorithm for Medical Image Segmentation

    Improved Reptile Search Algorithm by Salp Swarm Algorithm for Medical Image Segmentation by Abualigah, Laith

    Published 2023
    “…This study proposes a novel nature-inspired meta-heuristic optimizer based on the Reptile Search Algorithm combed with Salp Swarm Algorithm for image segmentation using gray-scale multi-level thresholding, called RSA-SSA. …”
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  13. 13
    Perceived Information Assurance in Conversational Systems

    Perceived Information Assurance in Conversational Systems by Alghannam, Bareeq

    Published 2026
    “…Through advanced feature engineering (117 features) and nature-inspired optimization algorithms, we achieved 98.38% classification accuracy. …”
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