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  1. 1
    Single-Solution Simulated Kalman Filter Algorithm for Global Optimisation Problems

    Single-Solution Simulated Kalman Filter Algorithm for Global Optimisation Problems by Nor Hidayati, Abdul Aziz, Zuwairie, Ibrahim, Nor Azlina, Ab. Aziz, Mohd Saberi, Mohamad, Watada, Junzo

    Published 2016
    “…This paper introduces single-solution Simulated Kalman Filter (ssSKF), a new single-agent optimisa- tion algorithm inspired by Kalman Filter, for solving real-valued numerical optimisation problems. …”
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  2. 2
    Single-solution Simulated Kalman Filter algorithm for global optimisation problems

    Single-solution Simulated Kalman Filter algorithm for global optimisation problems by Abdul Aziz, N.H., Ibrahim, Z., Ab Aziz, N.A., Mohamad, M.S., Watada, J.

    Published 2018
    “…This paper introduces single-solution Simulated Kalman Filter (ssSKF), a new single-agent optimisation algorithm inspired by Kalman Filter, for solving real-valued numerical optimisation problems. …”
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  3. 3
    Single-solution Simulated Kalman Filter algorithm for global optimisation problems

    Single-solution Simulated Kalman Filter algorithm for global optimisation problems by Abdul Aziz, N.H., Ibrahim, Z., Ab Aziz, N.A., Mohamad, M.S., Watada, J.

    Published 2018
    “…This paper introduces single-solution Simulated Kalman Filter (ssSKF), a new single-agent optimisation algorithm inspired by Kalman Filter, for solving real-valued numerical optimisation problems. …”
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  4. 4
    A simulation based fly optimisation algorithm for swarms of mini autonomous surface vehicles application

    A simulation based fly optimisation algorithm for swarms of mini autonomous surface vehicles application by Zainal Abidin, Zulkifli

    Published 2011
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  5. 5
    Simulation Of Path Optimisation Algorithms

    Simulation Of Path Optimisation Algorithms by Sim, Choon Yeee

    Published 2017
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    Monograph
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  6. 6
    Differential evolution for neural networks learning enhancement

    Differential evolution for neural networks learning enhancement by Ismail Wdaa, Abdul Sttar

    Published 2008
    “…Evolutionary computation is the name given to a collection of algorithms based on the evolution of a population toward a solution of a certain problem. …”
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  7. 7
    A New Quadratic Binary Harris Hawk Optimization For Feature Selection

    A New Quadratic Binary Harris Hawk Optimization For Feature Selection by Abdullah, Abdul Rahim, Too, Jing Wei, Mohd Saad, Norhashimah

    Published 2019
    “…In this study, twenty-two datasets collected from the UCI machine learning repository are used to validate the performance of proposed algorithms. A comparative study is conducted to compare the effectiveness of QBHHO with other feature selection algorithms such as binary differential evolution (BDE), genetic algorithm (GA), binary multi-verse optimizer (BMVO), binary flower pollination algorithm (BFPA), and binary salp swarm algorithm (BSSA). …”
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  8. 8
    Performance Comparison of FA, PSO and CS application in SINR Optimisation for LCMV Beamforming Technique

    Performance Comparison of FA, PSO and CS application in SINR Optimisation for LCMV Beamforming Technique by Doroody C., Kiong T.S.

    Published 2023
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  9. 9
    Hybrid firely and particle swarm optimisation algorithm for optimal dimming level and energy saving in lecturer’s room

    Hybrid firely and particle swarm optimisation algorithm for optimal dimming level and energy saving in lecturer’s room by Nik Ahmad, Nik Sahidah

    Published 2022
    “…To achieve the optimisation, a good, efficient and fast simulation algorithm is required. …”
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  10. 10
    Algorithmic design issues in adaptive differential evolution schemes: Review and taxonomy

    Algorithmic design issues in adaptive differential evolution schemes: Review and taxonomy by Al-Dabbagh, Rawaa Dawoud, Neri, Ferrante, Idris, Norisma, Baba, Mohd Sapiyan

    Published 2018
    “…A trend that has emerged recently is to make the algorithm parameters automatically adapt to different problems during optimization, thereby liberating the user from the tedious and time-consuming task of manual setting. …”
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  11. 11
    Feature selection optimization using hybrid relief-f with self-adaptive differential evolution

    Feature selection optimization using hybrid relief-f with self-adaptive differential evolution by Zainudin, Muhammad Noorazlan Shah, Sulaiman, Md. Nasir, Mustapha, Norwati, Perumal, Thinagaran, Ahmad Nazri, Azree Shahrel, Mohamed, Raihani, Abd Manaf, Syaifulnizam

    Published 2017
    “…Hence, feature selection is embedded to select the most meaningful features based on their rank. Differential evolution (DE) is one of the evolutionary algorithms that are widely used in various classification domains. …”
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  12. 12
    Smart grid: Bio-inspired algorithms energy distributions for data centers

    Smart grid: Bio-inspired algorithms energy distributions for data centers by Woo, Yu Hang

    Published 2025
    “…This project proposes and evaluates three bio-inspired and evolutionary algorithms for VM allocation and migration: Ant Colony Optimisation (ACO), Particle Swarm Optimisation (PSO), and a Modified Genetic Algorithm (MGA). …”
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    Final Year Project / Dissertation / Thesis
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  13. 13
    An Improved VEPSO Algorithm for Multi-objective Optimisation Problems

    An Improved VEPSO Algorithm for Multi-objective Optimisation Problems by Kamarul Hawari, Ghazali, Zuwairie, Ibrahim, Faradila, Naim, Kian, Sheng Lim, Salinda, Buyamin, Anita, Ahmad, Sophan Wahyudi, Nawawi, Norrima, Mokhtar

    Published 2015
    “…The vector evaluated particle swarm optimisation algorithm is widely used for such purpose, where this algorithm optimised one objective using one swarm of particles by the guidance from the best solution found by another swarm. …”
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  14. 14
    Artificial fish swarm optimization for multilayer network learning in classification problems

    Artificial fish swarm optimization for multilayer network learning in classification problems by Hasan, Shafaatunnur, Tan, Swee Quo, Shamsuddin, Siti Mariyam

    Published 2012
    “…Artificial Fish Swarm Algorithm (AFSA) as one of the NIC methods is widely used for optimizing the global searching of ANN.In this study, we applied the AFSA method to improve the Multilayer Perceptron (MLP) learning for promising accuracy in various classification problems.The parameters of AFSA: AFSA prey, AFSA swarm and AFSA follow are implemented on the MLP network for improving the accuracy of various classification datasets from UCI machine learning. …”
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  15. 15
    Artificial Fish Swarm Optmization for Multilayernetwork Learning in Classification Problems

    Artificial Fish Swarm Optmization for Multilayernetwork Learning in Classification Problems by Hasan, Shafaatunnur, Tan, Swee Quo, Shamsuddin, Siti Mariyam, Sallehuddin, Roselina

    Published 2012
    “…In this study, we applied the AFSA method to improve the Multilayer Perceptron (MLP) learning for promising accuracy in various classification problems. The parameters of AFSA: AFSA prey, AFSA swarm and AFSA follow are implemented on the MLP network for improving the accuracy of various classification datasets from UCI machine learning. …”
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  16. 16
    Genetic algorithm optimisation for fuzzy control of wheelchair lifting and balancing

    Genetic algorithm optimisation for fuzzy control of wheelchair lifting and balancing by Ahmad, Salmiah, Tokhi, M. Osman, Toha, Siti Fauziah

    Published 2009
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    Proceeding Paper
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  17. 17
    Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals

    Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals by Too, Jing Wei

    Published 2020
    “…Therefore, this thesis aims to solve the feature selection problem in EMG signals classification and improve the classification performance of EMG pattern recognition system. …”
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  18. 18
    Solving robot path planning problem using Ant Colony Optimisation (ACO) approach / Nordin Abu Bakar and Rosnawati Abdul Kudus

    Solving robot path planning problem using Ant Colony Optimisation (ACO) approach / Nordin Abu Bakar and Rosnawati Abdul Kudus by Abu Bakar, Nordin, Abdul Kudus, Rosnawati

    Published 2009
    “…Learning is a complex cognitive process; thus, the algorithms that can simulate learning are also complex. …”
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  19. 19
    Develpoment of combinatorial optimisation for cutting tool path strategy

    Develpoment of combinatorial optimisation for cutting tool path strategy by Alsultaney, Hazem K., Mohd Ariffin, Mohd Khairol Anuar, Baharudin, B. T. Hang Tuah, Ali, Aidy, Mustapha, Faizal

    Published 2009
    “…This work aims to optimise the tool path by simulating the removal of material in a finite element environment, which is controlled by a Genetic Algorithm. …”
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    Conference or Workshop Item
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  20. 20
    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. …”
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