Search Results - (( using estimation using algorithm ) OR ( using optimisation system algorithm ))

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  1. 1

    Augmented model based double iterative loop techniques for integrated system optimisation and parameter estimation of large scale industrial processes by Normah Abdullah, Brdys, M.A., Roberts, P.D.

    Published 1993
    “…The double iterative loop structures of the proposed algorithms use the real process measurement within the outer loops while the inner loops involve model based computation only. …”
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    Article
  2. 2

    Kernel and multi-class classifiers for multi-floor wlan localisation by Abd Rahman, Mohd Amiruddin

    Published 2016
    “…The multi-class classification strategy is used to ensure quick estimation of the multi-class NN algorithms. …”
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    Thesis
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    Novel techniques for voltage stability assessment and improvement in power system / Ismail Musirin. by Musirin, Ismail

    Published 2004
    “…A new Evolutionary programming (EP) based acceleration search algorithm was developed to accelerate the process in estimating maximum load ability in a power system. …”
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    Thesis
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    INTELLIGENT MODELLING OF GRADIENT FLEXIBLE PLATE STRUCTURE UTILISING HYBRID EVOLUTIONARY ALGORITHM by Muhammad Hasbollah, Hassan

    Published 2023
    “…First, evolutionary algorithms, namely particle swarm optimisation (PSO) and grey wolf optimisation (GWO) were used in developing GFPS dynamic model and their performances were compared. …”
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    Thesis
  7. 7

    Gait identification and optimisation for amphi-underwater robot by using ant colony algorithm by Mohd Yusof, Muhammad Syafiq, Toha @ Tohara, Siti Fauziah

    Published 2019
    “…For the optimization, the robot will travel from one specific point to another with the predefined position within optimized gait and fastest time by using Ant Colony Optimization (ACO) technique. The algorithm being compared, between Ant Colony Algorithm (ACO) and the Particle Swarm Optimisation (PSO) in terms of time and distance. …”
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    Article
  8. 8

    Sensorless Adaptive Fuzzy Logic Control Of Permanent Magnet Synchronous Motor by Hafz Nour, Mutasim Ibrahim

    Published 2008
    “…The output signal of the PI controller is added to the direct FLC output to compensate any deviations in the motor speed from the reference speed due to parameters variation and disturbances in the load. The design and optimisation of the FLC are carried out using an adaptive fuzzy inference system network that uses the backpropagation, least square and gradient algorithms. …”
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    Thesis
  9. 9

    Modeling water pH neutralisation behaviour in a small-scale hydroponic system using the NARX-PSO model / Mohammad Farid Saaid by Saaid, Mohammad Farid

    Published 2022
    “…This study also optimised parameters for the MLP-NARX model using the Particle Swarm Optimisation algorithm (PSO). …”
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    Thesis
  10. 10

    Development of energy storage system for storing regenerative braking energy from train by Faizal Zamani, Dollah

    Published 2022
    “…ETrax software is used for dynamic load flow simulations to obtain an accurate estimation of the energy recovery captured in the system in each operation mode by incorporating train headway interval variations, algorithm and the effects of train schedules on the operating mode.…”
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    Final Year Project / Dissertation / Thesis
  11. 11

    Grey wolf optimization for enhanced performance in wind power system with dual-star induction generators by Benamara K., Amimeur H., Hamoudi Y., Abdolrasol M.G.M., Cali U., Ustun T.S.

    Published 2025
    “…These algorithms play a crucial role in estimating the optimal values of Kp, Ki, and Kd for the PID speed controller, as well as Kp and Ki for the PI controller used in the flux, DC-link voltage, and grid connection for wind energy conversion system based dual-star induction generator. …”
    Article
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    Gravitational Search Algorithm Based LSTM Deep Neural Network for Battery Capacity and Remaining Useful Life Prediction With Uncertainty by Reza M.S., Hannan M.A., Mansor M.B., Ker P.J., Tiong S.K., Hossain M.J.

    Published 2025
    “…An accurate estimation of the remaining useful life (RUL) and capacity of lithium-ion batteries (LIBs) can guarantee safe and reliable operation and help to make wise replacement decisions. …”
    Article
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    Reliability assessment of power system generation adequacy with wind power using population-based intelligent search methods by Kadhem, Athraa Ali

    Published 2017
    “…The advantage of using these algorithms is obvious as they would speed up the computation to obtain higher accuracy with less computation effort. …”
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    Thesis
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    DeMI interface tool for profit estimation and waste conversion technology recommendations in enhancing municipal solid waste management by Ali, R.A., Nik Ibrahim, N.N.L., Ghani, W.A.W.A.K., Sani, N.S., Lam, H.L.

    Published 2024
    “…The M5P algorithm, adept at profit estimation, establishes correlations between MSW weight and profitability, while the J48 algorithm offers recommendations for suitable waste conversion technologies based on profit potential. …”
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    Article
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    New techniques incorporating computational intelligence based for voltage stability evaluation and improvement in power system / Nur Fadilah Ab. Aziz by Ab. Aziz, Nur Fadilah

    Published 2014
    “…Another new hybrid algorithm that used Evolutionary Programming (EP) termed as Evolutionary Support Vector Machine (ESVM) was also developed for comparative study. …”
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    Thesis
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    Application of optimized higher order sliding mode control on MEMS optical switch by Keramati, Ehsan, Teimoortashloo, Mazdak, Mohd Noor, Samsul Bahari

    Published 2012
    “…A Robust Exact Differentiator is used to estimate time derivatives of the sliding variable. …”
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    Conference or Workshop Item
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    Evaluating Adan vs. Adam: an analysis of optimizer performance in deep learning by Ismail, Amelia Ritahani, Azhary, Muhammad Zulhazmi Rafiqi, Hitam, Nor Azizah

    Published 2025
    “…Adaptive Moment Estimation (Adam) and Adaptive Nesterov Accelerated Gradi- ent (Adan), two well-known optimizers, are widely used in deep learning for their ability to handle large-scale data and complex models efficiently. …”
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    Proceeding Paper