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  1. 1
    Optimization of extractive Automatic Text Summarization using Decomposition-based Multi-objective Differential Evolution and parallelization

    Optimization of extractive Automatic Text Summarization using Decomposition-based Multi-objective Differential Evolution and parallelization by Hazmi Wahab, Muhammad Hafizul

    Published 2024
    “…The central challenge in Automatic Text Summarization (ATS) is efficiently generating machine-generated text summaries through optimization algorithms, a critical component for systems dealing with textual information processing. …”
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  2. 2
    ENGINEERING DESIGN WITH PSO ALGORITHM

    ENGINEERING DESIGN WITH PSO ALGORITHM by MHD BASIR, SITI NUR HAJAR

    Published 2019
    “…To optimise a mechanical design by the means of distance or even shape, it needs to these handle large numbers of variables, and optimal solution is needed to for such systems. …”
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  3. 3
    PMT : opposition based learning technique for enhancing metaheuristic algorithms performance

    PMT : opposition based learning technique for enhancing metaheuristic algorithms performance by Hammoudeh, S. Alamri

    Published 2020
    “…To evaluate the PMT’s performance and adaptability, the PMT was applied to four contemporary metaheuristic algorithms, Differential Evolution, Particle Swarm Optimization, Simulated Annealing, and Whale Optimization Algorithm, to solve 15 well-known benchmark functions as well as 2 real world problems based on the welded beam design and pressure vessel design. …”
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  4. 4
    PMT: opposition-based learning technique for enhancing meta-heuristic performance

    PMT: opposition-based learning technique for enhancing meta-heuristic performance by Alamri, Hammoudeh S., Kamal Z., Zamli

    Published 2019
    “…To evaluate the PMT's performance and adaptability, the PMT has been applied to four contemporary meta-heuristic algorithms, differential evolution (DE), particle swarm optimization (PSO), simulated annealing (SA), and whale optimization algorithm (WOA), to solve 15 well-known benchmark functions. …”
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  5. 5
    OPTIMIZATION OF HYBRID-FUZZY CONTROLLER FOR SERVOMOTOR CONTROL USING A MODIFIED GENETIC ALGORITHM

    OPTIMIZATION OF HYBRID-FUZZY CONTROLLER FOR SERVOMOTOR CONTROL USING A MODIFIED GENETIC ALGORITHM by WAHYUNGGORO, OYAS WAHYUNGGORO

    Published 2011
    “…In this thesis, a new optimization GA-based algorithm that emanates from modification of conventional GA to reduce the iterations number and the duration time, namely, semi-parallel operation genetic algorithm (SPOGA) is proposed. …”
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  6. 6
    Application Of Genetic Algorithms For Robust Parameter Optimization

    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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  7. 7
    Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm

    Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm by Hasan, Shafaatunnur, Tan, Swee Quo, Shamsuddin, Siti Mariyam, Sallehuddin, Roselina

    Published 2011
    “…Artificial Neural Network (ANN) is a new information processing system with large quantity of highly interconnected neurons or elements processing parallel to solve problems.Recently, evolutionary computation technique, Artificial Fish Swarm Algorithm (AFSA) is chosen to optimize global searching of ANN.In optimization process, each Artificial Fish (AF) represents a neural network with output of fitness value.The AFSA is used in this study to analyze its effectiveness in enhancing Multilayer Perceptron (MLP) learning compared to Particle Swarm Optimization (PSO) and Differential Evolution (DE) for classification problems.The comparative results indeed demonstrate that AFSA show its efficient, effective and stability in MLP learning.…”
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  8. 8
    Hybrid evolutionarybarnacles mating optimisation-artificial neural network based technique for solving economic power dispatch planning and operation / Nor Laili Ismail

    Hybrid evolutionarybarnacles mating optimisation-artificial neural network based technique for solving economic power dispatch planning and operation / Nor Laili Ismail by Ismail, Nor Laili

    Published 2024
    “…In this study, a new optimisation algorithm termed Hybrid Evolutionary-Barnacles Mating Optimisation (HEBMO) was initially formulated to solve optimisation problems. …”
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  9. 9
    Analyzing The Potential Of Genetic Algorithm For Maximum Power Point Tracking In Wind Energy Conversion System In Malaysia

    Analyzing The Potential Of Genetic Algorithm For Maximum Power Point Tracking In Wind Energy Conversion System In Malaysia by Nasrullah Bin Isnin

    Published 2023
    “…In this paper, a maximum power point tracking for the wind turbine is proposed which is the indirect speed control. A genetic algorithm is used to further optimised the control strategy by finding the optimised variable for the controller. …”
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  10. 10
    FPGA implementation of simulated kalman filter optimization algorithm

    FPGA implementation of simulated kalman filter optimization algorithm by Nurul Hazlina, Noordin, Zuwairie, Ibrahim, Xie, M. H.J., Rosdiyana, Samad, Nurulfadzilah, Hassan

    Published 2018
    “…This paper presents a novel FPGA implementation of the Simulated Kalman Filter Optimisation Algorithm. This system utilizes a distributed RAM to update the intermediate variables and the output of each iteration is stored in the block RAM. …”
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  11. 11
    Particle swarm optimisation for reactive power compensation on Oman 6 bus electrical grid

    Particle swarm optimisation for reactive power compensation on Oman 6 bus electrical grid by Al Mamari, Adnan Saif, Toha, Siti Fauziah, Ahmad, Salmiah, Al Mamari, Ali Salim

    Published 2021
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  12. 12
    A bacteria foraging algorithm for solving integrated multi-period cell formation and subcontracting production planning in a dynamic cellular manufacturing system

    A bacteria foraging algorithm for solving integrated multi-period cell formation and subcontracting production planning in a dynamic cellular manufacturing system by Tang, Sai Hong, Nouri, Hossein, Motlagh, Omid Reza Esmaeili

    Published 2011
    “…In addition, a newly-developed BFA-based optimisation algorithm has been compared with the branch and bound algorithm. …”
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  13. 13
    On the optimal control of the steel annealing processes as a two-stage hybrid systems via PSO algorithms

    On the optimal control of the steel annealing processes as a two-stage hybrid systems via PSO algorithms by Arumugam, M.S., Murthy, G.R., Loo, C.K.

    Published 2009
    “…The heating and soaking furnaces of the steel annealing line form the two-stage hybrid systems. Three algorithms including particle swarm optimisation (PSO) with globally and locally tuned parameters (GLBest PSO), a parameter free PSO algorithm (pf-PSO) and a PSO-like algorithm via extrapolated PSO (ePSO) are considered to solve this optimal control problem for the two-stage steel annealing processes (SAP). …”
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  14. 14
    Passive congregation theory for particle swarm optimization (PSO): An application in reservoir system operation

    Passive congregation theory for particle swarm optimization (PSO): An application in reservoir system operation by Hossain M.S., Mohd Sidek L.B., Marufuzzaman M., Zawawi M.H.

    Published 2023
    “…The passive congregation theory of natural being's social behaviour is adopted to updated the standard PSO algorithm and used to develop and optimise a reservoir release policy for monthly basis. …”
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  15. 15
    Multivariable adaptive lyapunov fuzzy controller for pH neutralisation process

    Multivariable adaptive lyapunov fuzzy controller for pH neutralisation process by Zanil, M.F., Hussain, Mohd Azlan

    Published 2015
    “…In this study, the nominal neutralisation process condition exhibit nonlinear dynamics and multi-delayed-effects input variables. The proposed controller uses a Takagi-Sugeno fuzzy inference system and it has been optimised by genetic algorithm which minimizing the closed loop error in feedback control system. …”
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  16. 16
    Multi-Objective Optimisation of CNC Milling Process for Al 6061 using Modified NSGA-II

    Multi-Objective Optimisation of CNC Milling Process for Al 6061 using Modified NSGA-II by M. F. F., Ab Rashid, N. M. Zuki, N. M., A. N. M., Rose

    Published 2016
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  17. 17
    Using Metaheuristics Algorithms (MHAs) to Optimize Water Supply Operation in Reservoirs: a Review

    Using Metaheuristics Algorithms (MHAs) to Optimize Water Supply Operation in Reservoirs: a Review by Almubaidin M.A.A., Ahmed A.N., Sidek L.B.M., Elshafie A.

    Published 2023
    “…Decision making; Heuristic algorithms; Optimization; Stochastic systems; Water supply; Complex problems; Decision variables; Meta-heuristics algorithms; Multiple constraint; Nonlinear problems; Optimisations; Variable constraints; Water deficits; Water supply operations; Waters resources; Reservoirs (water)…”
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  18. 18
    Multivariable Adaptive Lyapunov Fuzzy Controller for pH Neutralisation Process

    Multivariable Adaptive Lyapunov Fuzzy Controller for pH Neutralisation Process by Zanil, M.F., Hussain, Mohd Azlan

    Published 2015
    “…In this study, the nominal neutralisation process condition exhibit nonlinear dynamics and multi-delayed-effects input variables. The proposed controller uses a Takagi-Sugeno fuzzy inference system and it has been optimised by genetic algorithm which minimizing the closed loop error in feedback control system. …”
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  19. 19
    A Study of Postural Loading in Malaysian Mining Industry using Rapid Entire Body Assessment

    A Study of Postural Loading in Malaysian Mining Industry using Rapid Entire Body Assessment by M. F. F., Ab Rashid, N. M. Zuki, N. M., A. N., Mohd Rose

    Published 2016
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  20. 20
    Investigating The Performance Of Metaheuristics To Optimize The Revenue Of Semiconductor Supply Chain

    Investigating The Performance Of Metaheuristics To Optimize The Revenue Of Semiconductor Supply Chain by Roslee, Muhammad Sharifuddin

    Published 2022
    “…Investigating the performance of metaheuristics to optimise the revenue of the semiconductor supply chain is the final year project that focuses on to identify the supply chain shortage problem related to semiconductors and to compare among the 20 metaheuristics algorithm optimization programmes capable of optimising the semiconductor supply chain. …”
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