Search Results - intelligence based ((((swarm algorithm) OR (based algorithm))) OR (search algorithm))

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  1. 1
    Swarm Intelligence Based Protein Conformational Search Algorithm.

    Swarm Intelligence Based Protein Conformational Search Algorithm. by Bahamish, Hesham Awadh Abdallah, Abdullah, Rosni, Salam, Rosalina Abdul

    Published 2007
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  2. 2
    Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain

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

    Published 2018
    “…Multi-objective optimization problems are also addressed by proposing a modified multi-criterion optimization algorithm based on a Pareto-based Particle Swarm Optimization (PSO) algorithm called Multi-Objective Particle Swarm Optimization (MOPSO). …”
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  3. 3
    Bats echolocation-inspired algorithms for global optimisation problems

    Bats echolocation-inspired algorithms for global optimisation problems by Nafrizuan, Mat Yahya

    Published 2016
    “…The aim of the research is to introduce novel form of swarm intelligence algorithms based on real echolocation behaviour of bats. …”
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  4. 4
    Review of Multi-Objective Swarm Intelligence Optimization Algorithms

    Review of Multi-Objective Swarm Intelligence Optimization Algorithms by Yasear, Shaymah Akram, Ku Mahamud, Ku Ruhana

    Published 2021
    “…The MOO approaches include scalarization, Pareto dominance, decomposition and indicator-based. In this paper, the status of MOO research and state-of-the-art MOSI algorithms namely, multi-objective particle swarm, artificial bee colony, firefly algorithm, bat algorithm, gravitational search algorithm, grey wolf optimizer, bacterial foraging and moth-flame optimization algorithms have been reviewed. …”
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  5. 5
    Optimization and discretization of dragonfly algorithm for solving continuous and discrete optimization problems

    Optimization and discretization of dragonfly algorithm for solving continuous and discrete optimization problems by Bibi Amirah Shafaa, Emambocus

    Published 2024
    “…Swarm intelligence algorithms are metaheuristic algorithms inspired by the simple interactions of biological organisms in a population. …”
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  6. 6
    Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection

    Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection by Tubishat, Mohammad, Idris, Norisma, Shuib, Liyana, Abushariah, Mohammad A.M., Mirjalili, Seyedali

    Published 2020
    “…In addition, ISSA was compared with four well-known optimization algorithms such as Genetic Algorithm, Particle Swarm Optimization, Grasshopper Optimization Algorithm, and Ant Lion Optimizer. …”
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  7. 7
    Comparison of swarm intelligence algorithms for high dimensional optimization problems

    Comparison of swarm intelligence algorithms for high dimensional optimization problems by Bashath, Samar, Ismail, Amelia Ritahani

    Published 2018
    “…This paper presents a comprehensive study of two swarm intelligence based algorithms: 1- particle swarm optimization (PSO), 2-cuckoo search (CS).The two algorithms are analyzed and compared for problems consisting of high dimensions in respect of solution accuracy, and runtime performance by various classes of benchmark functions.…”
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  8. 8
    Improved particle swarm optimization by fast annealing algorithm

    Improved particle swarm optimization by fast annealing algorithm by Bashath, Samar, Ismail, Amelia Ritahani

    Published 2019
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  9. 9
    Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman

    Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman by Che Osman, Siti Eshah

    Published 2019
    “…In this study, a pattern based using Particle Swarm Optimization (PSO) is proposed named as Hexagon PSO (HPSO). …”
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  10. 10
    Swarm intelligence algorithms’ solutions to the travelling salesman’s problem

    Swarm intelligence algorithms’ solutions to the travelling salesman’s problem by Odili, Julius Beneoluchi, Noraziah, Ahmad, Roslina, Mohd Sidek

    Published 2020
    “…This paper presents research findings on the application of swarm intelligence techniques in computational intelligence to solve the travelling salesman’s problem. …”
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  11. 11
    Hybridization of enhanced ant colony system and Tabu search algorithm for packet routing in wireless sensor network

    Hybridization of enhanced ant colony system and Tabu search algorithm for packet routing in wireless sensor network by Husna, Jamal Abdul Nasir

    Published 2020
    “…Better performances were also achieved for success rate, throughput, and latency when compared to other hybrid routing algorithms such as Fish Swarm Ant Colony Optimization (FSACO), Cuckoo Search-based Clustering Algorithm (ICSCA), and BeeSensor-C. …”
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  12. 12
    Extended bat algorithm for PID controller tuning of wheeled mobile robot and swarm robotics target searching strategy

    Extended bat algorithm for PID controller tuning of wheeled mobile robot and swarm robotics target searching strategy by Nur Aisyah Syafinaz, Suarin

    Published 2020
    “…Extended Bat Algorithm (EBA) has been chosen as swarm intelligent based method for this research study. …”
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  13. 13
    A memory-based gravitational search algorithm for enhancing minimum variance distortionless response beamforming

    A memory-based gravitational search algorithm for enhancing minimum variance distortionless response beamforming by Darzi S., Sieh Kiong T., Tariqul Islam M., Rezai Soleymanpour H., Kibria S.

    Published 2023
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  14. 14
    Fruit-Fly Based Searching Algorithm For Cooperative Swarming Robotic System

    Fruit-Fly Based Searching Algorithm For Cooperative Swarming Robotic System by Abidin, Zulkifli Zainal

    Published 2013
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  15. 15
    Hybrid Intelligent Water Drops Algorithm For Examination Timetabling Problem

    Hybrid Intelligent Water Drops Algorithm For Examination Timetabling Problem by Bashar A.Aldeeb, Mohammed Azmi Al-Betar, Norita Md Norwawi, Khalid A.Alissa, Mutasem K.Alsmadi, Ayman A.Hazaymeh, Malek Alzaqebah

    Published 2024
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  16. 16
    Performance Comparison of FA, PSO and CS application in SINR Optimisation for LCMV Beamforming Technique

    Performance Comparison of FA, PSO and CS application in SINR Optimisation for LCMV Beamforming Technique by Doroody C., Kiong T.S.

    Published 2023
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  17. 17
    Swarm intelligence algorithms' solutions to the travelling salesman's problem

    Swarm intelligence algorithms' solutions to the travelling salesman's problem by Odili, Julius Beneoluchi, Noraziah, Ahmad, Roslina, Mohd Sidek

    Published 2020
    “…This paper presents research findings on the application of swarm intelligence techniques in computational intelligence to solve the travelling salesman's problem. …”
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  18. 18
    Virtual power plant and microgrids controller for energy management based on optimization techniques

    Virtual power plant and microgrids controller for energy management based on optimization techniques by Abdolrasol M.G.M., Mohamed A., Hannan M.A.

    Published 2023
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  19. 19
    Advances in Particle Swarm Algorithms in Asynchronous, Discrete and Multi-Objective Optimization

    Advances in Particle Swarm Algorithms in Asynchronous, Discrete and Multi-Objective Optimization by Zuwairie, Ibrahim

    Published 2014
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  20. 20
    Nature-inspired parameter controllers for ACO-based reactive search

    Nature-inspired parameter controllers for ACO-based reactive search by Sagban, Rafid, Ku-Mahamud, Ku Ruhana, Abu Bakar, Muhamad Shahbani

    Published 2015
    “…This study proposes machine learning strategies to control the parameter adaptation in ant colony optimization algorithm, the prominent swarm intelligence metaheuristic.The sensitivity to parameters’ selection is one of the main limitations within the swarm intelligence algorithms when solving combinatorial problems.These parameters are often tuned manually by algorithm experts to a set that seems to work well for the problem under study, a standard set from the literature or using off-line parameter tuning procedures. …”
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