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  1. 1

    Mixed-variable ant colony optimisation algorithm for feature subset selection and tuning support vector machine parameter by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2017
    “…This paper presents a hybrid classification algorithm, ACOMV-SVM which is based on ant colony and support vector machine.A new direction for ant colony optimisation is to optimise mixed (discrete and continuous) variables.The optimised variables are then feed into selecting feature subset and tuning its parameters are two main problems of SVM.Most approaches related to tuning support vector machine parameters will discretise the continuous value of the parameters which will give a negative effect on the performance. …”
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    Article
  2. 2

    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
  3. 3

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

    Published 2019
    “…Creating a PSO algorithm-based infrastructure integrating with the recommendation system will further enhance solution to the design problem. …”
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    Final Year Project
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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
  5. 5

    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
  6. 6

    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
  7. 7

    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
  8. 8

    Analytical Modelling And Efficiency Optimisation Of Permanent Magnet Synchronous Machine Using Particle Swarm Optimisation by Ling, Poh Ping

    Published 2018
    “…From PSO study, the four machine design variables has been simultaneously optimised and successfully produced parameters for a performance-optimised machine. …”
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    Thesis
  9. 9

    Dynamic Probability Selection for Flower Pollination Algorithm based on Metropolis-hastings Criteria by Zamli, Kamal Zuhairi, Din, Fakhrud, Nasser, Abdullah, Ramli, Nazirah, Mohamed, Noraini

    Published 2021
    “…This paper proposed flower pollination algorithm metropolis-hastings (FPA-MH) based on the adoption of Metropolis-Hastings criteria adopted from the Simulated Annealing (SA) algorithm to enable dynamic selection of the pa probability. …”
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    Article
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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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    Variable Neighbourhood Search Algorithm for Vehicle Routing Problem with Backhaul by Siaw Ying Doreen, Sek

    Published 2023
    “…Thus, a heuristic approach based on the Variable Neighbourhood Search (VNS) is proposed. …”
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    Thesis
  18. 18

    Aeronautical Revenues Optimisation Model (AROM) for regional airports via airside operations stochastic baseline matrix analysis / Wan Mazlina Wan Mohamed by Wan Mohamed, Wan Mazlina

    Published 2016
    “…The next objective concerns with the formulation of mathematical optimisation algorithm known as Aeronautical Revenue Optimisation Model (AROM) to generate maximum aeronautical revenues for regional airport in line with the objectives of the airport……”
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    Book Section
  19. 19

    An improved fair nurse scheduling optimisation using particle swarm intelligent technique by Ramli, Mohamad Raziff

    Published 2015
    “…A well-designed schedule algorithm shall be able to generate an efficient task that can precede the restriction and variability. …”
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    Thesis
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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