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  1. 1
    Global Particle Swarm Optimization for High Dimension Numerical Functions Analysis

    Global Particle Swarm Optimization for High Dimension Numerical Functions Analysis by Jamian, J.J., Abdullah, M.N., Mokhlis, Hazlie, Mustafa, M.W., Bakar, Ab Halim Abu

    Published 2014
    “…The Particle Swarm Optimization (PSO) Algorithm is a popular optimization method that is widely used in various applications, due to its simplicity and capability in obtaining optimal results. …”
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  2. 2
    Adapting the Elitism on the Greedy Algorithm for Variable Strength Combinatorial Test Cases Generation

    Adapting the Elitism on the Greedy Algorithm for Variable Strength Combinatorial Test Cases Generation by Bahomaid, Ameen A., Alsewari, Abdulrahman A., Zamli, Kamal Z., Alsariera, Yazan A.

    Published 2018
    “…This study presented the most recent variable interaction strength (VS) CT strategy using an enhanced variant in the greedy algorithm. …”
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  3. 3
    Harmony search-based robust optimal controller with prior defined structure

    Harmony search-based robust optimal controller with prior defined structure by Rafieishahemabadi, Ali

    Published 2013
    “…In this approach, a combination of interacting two levels HS optimization algorithm is presented. In the first level, a new method for analytical formulation of integral square error cost function based on controller variables is elaborated for performance evaluation purposes by the proposed optimization algorithm. …”
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  4. 4
    Loss Minimisation by Optimal Reactive Power Dispatch Using Cuckoo Search Algorithm

    Loss Minimisation by Optimal Reactive Power Dispatch Using Cuckoo Search Algorithm by M. H., Sulaiman, Muhammad Ikram, Mohd Rashid, Omar, Aliman, Mohd Rusllim, Mohamed, Abu Zaharin, Ahmad, Mohd. Shafie, Bakar

    Published 2014
    “…This paper presents a Swarm Intelligence (SI) technique namely Cuckoo Search Algorithm (CSA) which is inspired by parasitic behaviour of Cuckoo birds in reproduction strategy to obtain loss minimisation by solving the Optimal Reactive Power Dispatch (ORPD) problem. …”
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  5. 5
    Optimized differential evolution algorithm for linear frequency modulation radar signal denoising

    Optimized differential evolution algorithm for linear frequency modulation radar signal denoising by Al-Dabbagh, Mohanad Dawood Hasan

    Published 2013
    “…The main contention of this thesis is to investigate the development of new optimization technique based on Differential Evolution algorithm (DE), applied for radar signal denoising application. …”
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  6. 6
    A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification

    A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification by Talpur, N., Abdulkadir, S.J., Hasan, M.H., Alhussian, H., Alwadain, A.

    Published 2023
    “…The performance of the proposed SCSO algorithm was compared with six state-of-the-art and recent wrapper-based optimization algorithms using the validation metrics of classification accuracy, optimum feature size, and computational cost in seconds. …”
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  7. 7
    Optimization of Upstream Offshore Oilfield Production Planning under Uncertainty and Downstream Crude Oil Scheduling at Refinery Front-End

    Optimization of Upstream Offshore Oilfield Production Planning under Uncertainty and Downstream Crude Oil Scheduling at Refinery Front-End by Tan Yin Keong, Tan Yin

    Published 2012
    “…The optimization model is developed using GAMS and an optimal solution is found with no logical constraints conflicts or error. …”
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  8. 8
    Optimization of Upstream Offshore Oilfield Production Planning under Uncertainty and Downstream Crude Oil Scheduling at Refinery Front-End

    Optimization of Upstream Offshore Oilfield Production Planning under Uncertainty and Downstream Crude Oil Scheduling at Refinery Front-End by Tan , Yin Keong

    Published 2009
    “…The optimization model is developed using GAMS and an optimal solution is found with no logical constraints conflicts or error. …”
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  9. 9
    HABC: Hybrid artificial bee colony for generating variable T-way test sets

    HABC: Hybrid artificial bee colony for generating variable T-way test sets by Alazzawi, A.K., Rais, H.M., Basri, S.

    Published 2020
    “…This paper proposed a hybrid artificial bee colony (HABC) strategy based on the hybrid artificial bee colony algorithm and practical swarm optimization to generate optimal test suite of variable strength interaction. …”
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  10. 10
    HABC: Hybrid artificial bee colony for generating variable T-way test sets

    HABC: Hybrid artificial bee colony for generating variable T-way test sets by Alazzawi, A.K., Rais, H.M., Basri, S.

    Published 2020
    “…This paper proposed a hybrid artificial bee colony (HABC) strategy based on the hybrid artificial bee colony algorithm and practical swarm optimization to generate optimal test suite of variable strength interaction. …”
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  11. 11
    Crossover and mutation operators of real coded genetic algorithms for global optimization problems

    Crossover and mutation operators of real coded genetic algorithms for global optimization problems by Lim, Siew Mooi

    Published 2016
    “…The rationale behind developing algorithms using real encoding of chromosome representations is the limitations of binary encoding. …”
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  12. 12
    A review on particle swarm optimization algorithm and its variants to human motion tracking

    A review on particle swarm optimization algorithm and its variants to human motion tracking by Saini, S., Rambli, D.R.B.A., Zakaria, M.N.B., Sulaiman, S.B.

    Published 2014
    “…Particle swarm optimization (PSO) is a population-based globalized search algorithm which has been successfully applied to address human motion tracking problem and produced better results in high-dimensional search space.This paper presents a systematic literature survey on the PSO algorithm and its variants to human motion tracking. …”
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  13. 13
    Modelling knowledge transfer of nursing students during clinical placement / Nor Azairiah Fatimah Othman

    Modelling knowledge transfer of nursing students during clinical placement / Nor Azairiah Fatimah Othman by Othman, Nor Azairiah Fatimah

    Published 2017
    “…The application of the proposed algorithm has been justified as the most accurate with lower computation time as compared to other optimization techniques such as evolutionary programming (EP) and artificial immune system (AIS). …”
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  14. 14
    Non-weighted aggregate evaluation function of multi-objective optimization for knock engine modeling

    Non-weighted aggregate evaluation function of multi-objective optimization for knock engine modeling by Witwit, Azher Razzaq Hadi

    Published 2017
    “…It also aims to optimize the nonlinear nature of the factors by using Genetic Algorithm (GA) as well as investigate the behavior of such function. …”
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  15. 15
    Mobile data gathering algorithms for wireless sensor networks

    Mobile data gathering algorithms for wireless sensor networks by Ghaleb, Mukhtar Mahmoud Yahya

    Published 2014
    “…The third proposed algorithm achieves an adaptive data gathering strategy. …”
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  16. 16
    PID-PSO DC motor position controller design for ankle rehabilitation system

    PID-PSO DC motor position controller design for ankle rehabilitation system by Azizi, Muhammad Azizul Raziq

    Published 2023
    “…The transfer function is a model in Matlab software to validate the performance of the control system through simulation compared with real-time experiments. Next, the control algorithms are proposed to design and implement the Proportional-Integral-Derivative (PID) with Particle Swarm Optimization (PSO) controller technique for optimal Proportional (Kp), Integral (Ki) and Derivative (Kd) gains. …”
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  17. 17
    Model Predictive Control Design for f Nonlinear Four-Tank System

    Model Predictive Control Design for f Nonlinear Four-Tank System by Ansarpanahi, Shadi

    Published 2008
    “…The problems of complexity of algorithm, non-convexity of the optimization, especially when working with nonlinear plants are the most common problems in the control design criteria. …”
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  18. 18
    Groundwater quality assessment and optimization of monitored wells using multivariate geostatistical techniques in Amol-Babol Plain, Iran

    Groundwater quality assessment and optimization of monitored wells using multivariate geostatistical techniques in Amol-Babol Plain, Iran by Narany, Tahoora Sheikhy

    Published 2015
    “…DRASTIC model was applied as a vulnerability assessment method based on the physical environmental aquifer parameters for assessing potential risk zone of aquifer to contamination, which showed more than 88% of the total area was classified as low to moderate risk to pollutant. A new optimization approach was proposed for redesign monitoring network wells using optimization algorithm based on the vulnerability of aquifer to contaminations, estimation error of sampling wells, nearest distance between wells, and source of contamination in the study area. …”
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  19. 19
    Network reconfiguration and DG sizing incorporating optimal switching sequence for system improvement / Ola Subhi Waheed Badran

    Network reconfiguration and DG sizing incorporating optimal switching sequence for system improvement / Ola Subhi Waheed Badran by Ola Subhi , Waheed Badran

    Published 2018
    “…The proposed network reconfiguration also considered load profiles, DG output generation, DG types, and DG operating mode to decrease the total daily power loss. The chosen optimization techniques in this work include evolutionary programming (EP), particle swarm optimization (PSO), gravitational Search Algorithm (GSA), and firefly algorithm (FA). …”
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  20. 20
    Development of a motion planning and obstacle avoidance algorithm using adaptive neuro fuzzy inference system for mobile robot navigation

    Development of a motion planning and obstacle avoidance algorithm using adaptive neuro fuzzy inference system for mobile robot navigation by Muslim, Farah Kamil Abid

    Published 2017
    “…Finally, the last objective is to improve the optimality of the new approach using a robust Machine Learning strategy. …”
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