Search Results - (( knowledge optimization based algorithm ) OR ( parameter optimisation _ algorithm ))

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  1. 1

    Fuzzy genetic algorithms for combinatorial optimisation problems by Varnamkhasti, Mohammad Jalali

    Published 2012
    “…Fuzzy Logic Controllers (FLCs) are considered as knowledge-based systems, incorporating human knowledge. …”
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    Thesis
  2. 2

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

    Published 2023
    “…Deep reinforcement learning is a self-learning algorithm through trial and error and experience, without any prior knowledge. …”
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    Thesis
  3. 3

    Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things by Hadi, Ahmed Adnan

    Published 2022
    “…Hence, the algorithm must overcome the problem of dynamic updates in the internal parameters or counter the concept drift. …”
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    Thesis
  4. 4

    Modelling and calibration of high-pressure direct injection compressed natural gas engine by Mohd Fadzil, Abdul Rahim

    Published 2021
    “…The calibration framework consists of the development of the data-driven model by using ANN and ECU parameters optimisation by using GA. Based on stated methodologies, the following findings were recorded; the analytical model of the HPDI-CNG vehicle predicted a maximum of 123.11 Nm of brake torque at 60 bar of injection pressure. …”
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    Thesis
  5. 5

    Gravitational energy harvesting system based on multistage braking technique for multilevel elevated car parking building by Al Kubaisi, Yasir Mahmood

    Published 2020
    “…Thirdly, modeling of electrical and mechanical parameters for the presented system such that the system performance matching the model, this process is performed by using a parameter optimization algorithm. …”
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    Thesis
  6. 6

    A review: Use of evolutionary algorithm for optimisation of machining parameters by Zolpakar, N. A., Mohd Fuad, Yasak, Pathak, Sunil

    Published 2021
    “…Lately, evolutionary algorithm, statistical approaches such as genetic algorithm (GA), particle swarm optimisation (PSO), and cuckoo search algorithm (CSA) have been utilised in simultaneous optimisation of the parameters of the desired outputs and its great potential in optimising machining processes is recognisable.…”
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    Article
  7. 7

    PSO-LFDE Algorithm on Constrained Real-Parameter Optimisation Test Functions by Nafrizuan, Mat Yahya, Nur Iffah, Mohamed Azmi

    Published 2023
    “…The proposed PSO-LFDE algorithm is compared with the PSO algorithm by Gaing on single-objective constrained real-parameter optimisation test functions. …”
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    Conference or Workshop Item
  8. 8

    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
  9. 9

    Optimization Of Pid Controller Using Grey Wolf Optimzer And Dragonfly Algorithm by Nik Mohamed Hazli, Nik Muhammad Aiman

    Published 2018
    “…Optimisation is difficult to optimise as there are three parameters that need to be tuned, Kp, Integral parameter, Ki, and derivative parameter, Kd. …”
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    Monograph
  10. 10

    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
    “…The proposed method combined the improved teaching-learning-based optimisation (ITLBO) algorithm, improved parallel JAYA (IPJAYA) algorithm, and support vector machine. …”
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    Article
  11. 11

    Optimisation of Surface Roughness in 3D Printing Using the Bees Algorithm by Kamaruddin, Shafie, Ridzuan, Arman Hilmi, Sukindar, Nor Aiman

    Published 2025
    “…This study uses the Bees Algorithm to predict the best combination parameters to optimise the surface roughness of parts printed by a fused deposition modelling (FDM) machine. …”
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    Book Chapter
  12. 12

    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
    “…The proposed ssSKF algorithm is tested using the 30 benchmark functions of CEC 2014, and its performance is compared to the original SKF algorithm, Black Hole (BH) algorithm, Particle Swarm Optimisation (PSO) algorithm, Grey Wolf Optimiser (GWO) algorithm, and Genetic Algorithm (GA). …”
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    Article
  13. 13

    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
    “…The proposed ssSKF algorithm is tested using the 30 benchmark functions of CEC 2014, and its performance is compared to that of the original SKF algorithm, Black Hole (BH) algorithm, Particle Swarm Optimisation (PSO) algorithm, Grey Wolf Optimiser (GWO) algorithm and Genetic Algorithm (GA). …”
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    Article
  14. 14

    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
    “…The proposed ssSKF algorithm is tested using the 30 benchmark functions of CEC 2014, and its performance is compared to that of the original SKF algorithm, Black Hole (BH) algorithm, Particle Swarm Optimisation (PSO) algorithm, Grey Wolf Optimiser (GWO) algorithm and Genetic Algorithm (GA). …”
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    Article
  15. 15

    Parameter Estimation Using Improved Differential Evolution And Bacterial Foraging Algorithms To Model Tyrosine Production In Mus Musculus(Mouse) by Jia, Xing Yeoh, Chuii, Khim Chong, Mohd Saberi, Mohamad, Yee, Wen Choon, Lian, En Chai, Safaai, Deris, Zuwairie, Ibrahim

    Published 2015
    “…The hybrid of Differential Evolution algorithm with Kalman Filtering and Bacterial Foraging algorithm is a novel global optimisation method implemented to obtain the best kinetic parameter value. …”
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    Article
  16. 16

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

    Published 2009
    “…Genetic Algorithm is used to control the two-wheeled wheelchair and results show that the optimised parameters give better system performance.…”
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    Proceeding Paper
  17. 17

    Sustainable Management Of River Water Quality Using Artificial Intelligence Optimisation Algorithms by Chia, See Leng

    Published 2021
    “…Among the hybrid models, in terms of accuracy, the best optimisation algorithm at station 1K06 was the AMFO while the best optimisation algorithm at station 1K07 was the HPSOGA. …”
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    Final Year Project / Dissertation / Thesis
  18. 18
  19. 19

    Optimisation of automatic generation control performance in two-area power system with pid controllers using mepso / Lu Li by Lu , Li

    Published 2018
    “…Therefore, via implementation of optimisation method, the performance of AGC can be improved by varying the parameters of PID controller.…”
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    Thesis
  20. 20

    Analysis of Strength on Thick Plate Part using Genetic Algorithm Optimisation Method by S. M., Azlan, Z., Shayfull, S. M., Nasir, Mohd Sazli, Saad, Mohd Rashidi, Maarof, M., Fathullah

    Published 2016
    “…This study focuses on the optimisation of the injection moulding parameters to maximise the strength ofmoulded parts using a simulation software. …”
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    Conference or Workshop Item