Search Results - (( using optimisation system algorithm ) OR ( parameter optimization technique 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
    “…Two novel hierarchical structures are presented which extend the applicability of previous model based double iterative loop techniques to non-convex problems. The methods incorporate integrated system optimisation and parameter estimation which utilizes process measurements to achieve real process optimality inspite of model reality differences. …”
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    Article
  2. 2

    Design of low order quantitative feedback theory and H-infinity-based controllers using particle swarm optimisation for a pneumatic actuator system by Ali, Hazem I.

    Published 2010
    “…These algorithms are designed to achieve the robustness over a wide range of system parameters change and disturbances. …”
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    Thesis
  3. 3

    Performance Comparison of Particle Swarm Optimization and Gravitational Search Algorithm to the Designed of Controller for Nonlinear System by Md Rozali, Sahazati, Rahmat, Mohd Fua'ad, Husain, Abdul Rashid

    Published 2014
    “…This paper presents backstepping controller design for tracking purpose of nonlinear system. Since the performance of the designed controller depends on the value of control parameters, gravitational search algorithm (GSA) and particle swarm optimization(PSO) techniques are used to optimise these parameters in order to achieve a predefined system performance. …”
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    Article
  4. 4

    Firefly analytical hierarchy algorithm for optimal allocation and sizing of distributed generation in radial distribution network by Bujal, Noor Ropidah

    Published 2022
    “…The results showed that the Firefly Algorithm (FA) performs much better for the optimal allocation and sizing of DG compared to the other metaheuristic techniques, particularly based on convergence characteristics and standard deviation. …”
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    Thesis
  5. 5

    ANFIS modelling of a twin rotor system using particle swarm optimisation and RLS by Toha, Siti Fauziah, Tokhi, M. O.

    Published 2010
    “…The antecedent parameters of the ANFIS are optimized by a PSO algorithm and the consequent parameters are updated using recursive least squares (RLS). …”
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    Proceeding Paper
  6. 6

    Firefly optimised PID control for upper extremity rehabilitation robot by Joyo, M. Kamran, Raza, Yarooq, Kadir, Kushsairy, Naidu, Kanendra, Ahmed, Syed Faiz, Khan, Sheroz

    Published 2020
    “…This paper proposes a meta-heuristic technique to optimize controller parameters for upper extremity rehabilitation robot. …”
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    Proceeding Paper
  7. 7

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

    Published 2013
    “…Moreover, the ant colony optimisation technique be applied as an expert algorithm to make a decision for the selection of optimal features in order to enhance the performance of a classifier for recognition of diverse species of plants. …”
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    Thesis
  8. 8

    Optimal algorithms for the charge equalisation controller of series connected lithium-ion battery cells in electric vehicle applications by Hoque M.M., Hannan M.A., Mohamed A.

    Published 2023
    “…Charging (batteries); Controllers; Electric batteries; Electric machine control; Electric vehicles; Equalizers; Optimization; Particle swarm optimization (PSO); Secondary batteries; Voltage control; Control techniques; Discontinuous current mode; Flyback converters; Optimal algorithm; Particle swarm optimisation; PI controller parameters; Switching signals; Vehicle applications; Lithium-ion batteries…”
    Article
  9. 9
  10. 10

    An optimization method of genetic algorithm for lssvm in medium term electricity price forecasting by Abdul Razak I.A.W., Abidin I.Z., Siah Y.K., Abidin A.A.Z., Rahman T.K.A., Baharin N., Jali H.B.

    Published 2023
    “…This is due to the limited historical data for training and testing purposes. Therefore, an optimisation technique of Genetic Algorithm (GA) for Least Square Support Vector Machine (LSSVM) was developed in this study to provide an accurate electricity price forecast with optimised LSSVM parameters and input features. …”
    Article
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  12. 12

    Optimization and assessment of substation grounding grid designs in non-homogeneous soil conditions by Navinesshani A/P Permal, Dr.

    Published 2023
    “…An optimisation method established from the Simulated Annealing (SA) algorithm is applied to search for an optimal grounding design solution. …”
    text::Thesis
  13. 13

    Modelling of optimized hybrid debris flow using airborne laser scanning data in Malaysia by Lay, Usman Salihu

    Published 2019
    “…The general objective of the study was the development of optimized hybrid debris flow models using airborne laser scanning data and Machine learning algorithms in Malaysia. …”
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    Thesis
  14. 14

    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
  15. 15

    Recent Development of Grid-Connected Microgrid Scheduling Controllers for Sustainable Energy: A Bibliometric Analysis and Future Directions by Mannan M., Mansor M., Reza M.S., Roslan M.F., Ker P.J., Hannan M.A.

    Published 2025
    “…This study presents a comprehensive bibliometric analysis of grid-connected microgrid (MG) scheduling controller techniques. An extensive search was done in the Scopus database using preset parameters to extract articles relating to the MG scheduling controller. …”
    Article
  16. 16

    Prioritisation assessment and robust predictive model for a comprehensive medical equipment maintenance using machine learning techniques / Aizat Hilmi Zamzam by Aizat Hilmi, Zamzam

    Published 2022
    “…The development of predictive models for objectives 1 and 2 of this study involves the application of seven supervised machine learning algorithms. The effectiveness of these models is assessed through eleven performance evaluation parameters. …”
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    Thesis
  17. 17

    Mathematical modelling and hybrid ACO-PSO technique for PV performance improvement by Ali Mahmood, Humada

    Published 2016
    “…Secondly, a hybrid Ant Colony Optimisation-Particle Swarm Optimisation (ACO-PSO) algorithm was proposed to optimally determine the MPPT parameters. …”
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    Thesis
  18. 18

    Artificial neural networks based optimization techniques: A review by Abdolrasol M.G.M., Suhail Hussain S.M., Ustun T.S., Sarker M.R., Hannan M.A., Mohamed R., Ali J.A., Mekhilef S., Milad A.

    Published 2023
    “…In the last few years, intensive research has been done to enhance artificial intelligence (AI) using optimization techniques. In this paper, we present an extensive review of artificial neural networks (ANNs) based optimization algorithm techniques with some of the famous optimization techniques, e.g., genetic algorithm (GA), particle swarm optimization (PSO), artificial bee colony (ABC), and backtracking search algorithm (BSA) and some modern developed techniques, e.g., the lightning search algorithm (LSA) and whale optimization algorithm (WOA), and many more. …”
    Review
  19. 19

    LS-SVM Hyper-parameters Optimization Based on GWO Algorithm for Time Series Forecasting by Zuriani, Mustaffa, Mohd Herwan, Sulaiman, M. N. M., Kahar

    Published 2015
    “…In this study, a new metaheuristic algorithm, viz., Grey Wolf Optimizer (GWO), is employed to optimize the parameters of interest. …”
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    Conference or Workshop Item
  20. 20

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

    Published 2018
    “…In this research, swarming intelligence is used to solve optimisation problem. Grey Wolf Optimizer and Dragonfly Algorithm were chosen. …”
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    Monograph