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  1. 1
    The Bacterial Foraging Optimisation Algorithm using Prototype Selection and Prototype Generation for Data Classification

    The Bacterial Foraging Optimisation Algorithm using Prototype Selection and Prototype Generation for Data Classification by Faizol, Bin Mohd Suria

    Published 2020
    “…A new emerging nature-inspired algorithm named Bacterial Foraging Optimisation Algorithm (BFOA) that mimics the foraging behaviour of E. coli bacteria has drawn lots of attention from other researchers due to its high convergence rate and global search capability compared to others. …”
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  2. 2
    A New Bats Echolocation-based Algorithm for Single Objective Optimisation

    A New Bats Echolocation-based Algorithm for Single Objective Optimisation by N. M., Yahya, Tokhi, M. Osman, Kasdirin, Hyreil Anuar

    Published 2016
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  3. 3
    Intergrated multi-objective optimisation of assembly sequence planning and assembly line balancing using particle swarm optimisation

    Intergrated multi-objective optimisation of assembly sequence planning and assembly line balancing using particle swarm optimisation by M. F. F., Ab Rashid

    Published 2013
    “…The aim of this research is to establish a methodology and algorithm for integrating ASP and ALB optimisation using Particle Swarm Optimisation. …”
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  4. 4
    Position score weighting technique for mining web content outliers.

    Position score weighting technique for mining web content outliers. by Mustapha, Norwati, Mustapha, Aida

    Published 2013
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  5. 5
    Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System

    Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System by Aljanabi, Mohammad, Mohd Arfian, Ismail, Mezhuyev, Vitaliy

    Published 2020
    “…Many optimisation-based intrusion detection algorithms have been developed and are widely used for intrusion identification. …”
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  6. 6
    Optimisation of fed-batch fermentation process using deep reinforcement learning

    Optimisation of fed-batch fermentation process using deep reinforcement learning by Chai, Wan Ying

    Published 2023
    “…The proposed deep reinforcement learning algorithm, which integrates an artificial neural network with traditional reinforcement learning, was formulated based on the optimisation objective by manipulating only the substrate feeding rate. …”
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  7. 7
    A web usage mining approach based on LCS algorithm in online predicting recommendation systems

    A web usage mining approach based on LCS algorithm in online predicting recommendation systems by Jalali, Mehrdad, Mustapha, Norwati, Sulaiman, Md. Nasir, Mamat, Ali

    Published 2008
    “…Online prediction is one Web Usage Mining application. However, the accuracy of the prediction and classification in the current architecture of predicting users' future requests systems can not still satisfy users especially in huge Web sites. …”
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  8. 8
    Bees algorithm enhanced with Nelder and Mead method for numerical function optimisation

    Bees algorithm enhanced with Nelder and Mead method for numerical function optimisation by Kamaruddin, Shafie, Bahari, Muhammad Syahril, Pham, Duc Truong, Mohd Amin Hamzas, Mohd Fidzwan, Zakaria, S

    Published 2019
    “…The Bees Algorithm is a population-based optimisation algorithm inspired by the food foraging behaviour of honey bees. …”
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  9. 9
    Exothermic batch process optimisation via multivariable genetic algorithm

    Exothermic batch process optimisation via multivariable genetic algorithm by Tan, Min Keng, Chuo, Helen Sin Ee, Tham, Heng Jin, Teo, Kenneth Tze Kin

    Published 2012
    “…This paper aims optimise the exothermic batch productivity while minimise the waste production by manipulating the fluid temperature and fluid flow rate. …”
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  10. 10
    Optimising neural network training efficiency through spectral parameter-based multiple adaptive learning rates

    Optimising neural network training efficiency through spectral parameter-based multiple adaptive learning rates by Yeong, Lin Koay, Hong, Seng Sim, Yong, Kheng Goh, Sing, Yee Chua, Wah, June Leong

    Published 2024
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  11. 11
    Plant leaf recognition algorithm using ant colony-based feature extraction technique

    Plant leaf recognition algorithm using ant colony-based feature extraction technique by Ghasab, Mohammad Ali Jan

    Published 2013
    “…Then, based on the characteristics of each species, decision making is done by means of ant colony optimisation as a search algorithm to return the optimal subset of features regarding the related species. …”
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  12. 12
    An extended ID3 decision tree algorithm for spatial data

    An extended ID3 decision tree algorithm for spatial data by Sitanggang, Imas Sukaesih, Yaakob, Razali, Mustapha, Norwati, Nuruddin, Ahmad Ainuddin

    Published 2011
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  13. 13
    Enhanced convergence of Bat Algorithm based on dimensional and inertia weight factor

    Enhanced convergence of Bat Algorithm based on dimensional and inertia weight factor by Ramli, Mohamad Raziff, Abal Abas, Zuraida, Desa, Mohammad Ishak, Zainal Abidin, Zaheera, Al Azzam, Malik Bader Hasan

    Published 2019
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  14. 14
    Deep learning optimisation algorithms for snatch theft detection / Nurul Farhana Mohamad Zamri ...[et al.]

    Deep learning optimisation algorithms for snatch theft detection / Nurul Farhana Mohamad Zamri ...[et al.] by Mohamad Zamri, Nurul Farhana, Md Tahir, Nooritawati, Megat Ali, Megat Syahirul Amin, Khirul Ashar, Nur Dalila

    Published 2022
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  15. 15
    Colour Image Enhancement Model of Retinal Fundus Image for Diabetic Retinopathy Recognition

    Colour Image Enhancement Model of Retinal Fundus Image for Diabetic Retinopathy Recognition by Mohd Sharif, Nurul Atikah, Harun, Nor Hazlyna, Yusof, Yuhanis

    Published 2024
    “…Secondly, based on hybrid particle swarm optimisation-contrast stretch (HPSOCS), the hybrid of TBCSSR and HPSOCS named eTBCSSR-HPSOCS algorithm is introduced to tackle the limitations of the standard Particle Swarm Optimisation (PSO) algorithm in HPSOCS, which is prone to local optima and exhibits low convergence rates. …”
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  16. 16
    Distributed learning based energy-efficient operations in small cell networks

    Distributed learning based energy-efficient operations in small cell networks by Mughees, Amna

    Published 2023
    “…Simulation results demonstrate improved performance in power consumption, load, sum rate, utility, learning rate, convergence, and energy efficiency for small base stations (SBSs) and user equipment (UEs) compared to four benchmarked algorithms, including WMMSE, game theory, Q-learning, and DRL. …”
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  17. 17
    Adapting And Hybridising Harmony Search With Metaheuristic Components For University Course Timetabling

    Adapting And Hybridising Harmony Search With Metaheuristic Components For University Course Timetabling by Al-Betar, Mohammed Azmi

    Published 2010
    “…The major thrust of this algorithm lies in its ability to integrate the key components of populationbased methods and local search-based methods in the same optimisation model. …”
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  18. 18
    Modelling and optimisation of blood glucose control for type 1 diabetes using multi-parametric programming and model-based predictive control (mp-MPC) / Associate Professor Dr Ayub Md. Som

    Modelling and optimisation of blood glucose control for type 1 diabetes using multi-parametric programming and model-based predictive control (mp-MPC) / Associate Professor Dr Ayub... by Md. Som, Ayub

    Published 2014
    “…In doing so, Multi-Parametric Programming technique is used to develop the computer algorithm; whereas Model-Based Predictive Control (MPC) is adopted for the design of the controller. …”
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  19. 19
    Wireless network power optimization using relay stations blossoming and withering technique

    Wireless network power optimization using relay stations blossoming and withering technique by Al-Samawi, Aida, Sali, A., Nissirat, Liyth Ahmad, Noordin, Nor Kamariah, Othman, Mohamed, Hashim, Fazirulhisyam

    Published 2017
    “…Moreover, relative relay to base station capacity parameter is defined, and its effect on the power optimisation is investigated. …”
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  20. 20
    Energy and Cost Integration for Multi-Objective Optimisation in a Sustainable Turning Process

    Energy and Cost Integration for Multi-Objective Optimisation in a Sustainable Turning Process by Bagaber, Salem Abdullah, A. R., Yusoff

    Published 2018
    “…This paper aims to improve a sustainable cutting process through the integration of energy and cost modeling. The solution is based on the multi-objective optimisation of cutting parameters, including cutting speed, feed rate and cutting depth, based energy, cost and quality processes. …”
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