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    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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    Final Year Project
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    Improved whale optimization algorithm for feature selection in Arabic sentiment analysis by Tubishat, Mohammad, Abushariah, Mohammad A.M., Idris, Norisma, Aljarah, Ibrahim

    Published 2019
    “…In SA, feature selection phase is an important phase for machine learning classifiers specifically when the datasets used in training is huge. Whale Optimization Algorithm (WOA) is one of the recent metaheuristic optimization algorithm that mimics the whale hunting mechanism. …”
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    Article
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    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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    Thesis
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    Time series predictive analysis based on hybridization of meta-heuristic algorithms by Mustaffa, Zuriani, Sulaiman, Mohd Herwan, Rohidin, Dede, Ernawan, Ferda, Kasim, Shahreen

    Published 2018
    “…The identified meta-heuristic methods namely Moth-flame Optimization (MFO), Cuckoo Search algorithm (CSA), Artificial Bee Colony (ABC), Firefly Algorithm (FA) and Differential Evolution (DE) are individually hybridized with a well-known machine learning technique namely Least Squares Support Vector Machines (LS-SVM). …”
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    Article
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    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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    Classification with degree of importance of attributes for stock market data mining by Khokhar, Rashid Hafeez, Md. Sap, Mohd. Noor

    Published 2004
    “…Alan Fan et aI., [2] use Support Vector Machine (SVM) to stock market prediction. The SVM is a training algorithm for learning classification and regression rules from data [7]. …”
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    Article
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    Time series predictive analysis based on hybridization of meta-heuristic algorithms by Zuriani, Mustaffa, M. H., Sulaiman, Rohidin, Dede, Ernawan, Ferda, Shahreen, Kasim

    Published 2018
    “…The identified meta-heuristic methods namely Moth-flame Optimization (MFO), Cuckoo Search algorithm (CSA), Artificial Bee Colony (ABC), Firefly Algorithm (FA) and Differential Evolution (DE) are individually hybridized with a well-known machine learning technique namely Least Squares Support Vector Machines (LS-SVM). …”
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    Article
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    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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    Article
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    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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    Article
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    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. …”
    Article
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    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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    Conference or Workshop Item
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    Stock market turning points rule-based prediction / Lersak Photong … [et al.] by Photong, Lersak, Sukprasert, Anupong, Boonlua, Sutana, Ampant, Pravi

    Published 2021
    “…Finally, rule-based optimisation techniques such as Particle Swarm Optimization (PSO), Differential Evolution (DE) and Grey Wolf Optimizer (GWO) were used to minimise the amount of time employed in the stock market turning points prediction. …”
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    Book Section
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    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)…”
    Review
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    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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    Article
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    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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    Monograph
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