Search Results - (( parameter evaluation model algorithm ) OR ( parameter optimisation based algorithm ))

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  1. 1
    A comparative evaluation of PID-based optimisation controller algorithms for DC motor

    A comparative evaluation of PID-based optimisation controller algorithms for DC motor by Ahamed S.R., Parumasivam P., Hossain Lipu M.S., Hannan M.A., Ker P.J.

    Published 2023
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  2. 2
    Optimisation of laser cutting parameters of oil palm wood / Harizam Mohd Zin

    Optimisation of laser cutting parameters of oil palm wood / Harizam Mohd Zin by Harizam, Mohd Zin

    Published 2013
    “…In some cases, the prediction errors of Taguchi ANN model was found larger than 10% even using a Levenberg Marquardt training algorithm. …”
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  3. 3
    Development of soft computing prediction model for the influent physicochemical characteristics of sewage treatment plants / Mozafar Ansari

    Development of soft computing prediction model for the influent physicochemical characteristics of sewage treatment plants / Mozafar Ansari by Mozafar , Ansari

    Published 2021
    “…The best algorithm for each parameter was selected based on these criteria. …”
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  4. 4
    Completion time driven hyper-heuristic approach for optimisation of scientific workflow scheduling in cloud environment / Ehab Nabiel Mohammad

    Completion time driven hyper-heuristic approach for optimisation of scientific workflow scheduling in cloud environment / Ehab Nabiel Mohammad by Ehab Nabiel , Mohammad

    Published 2018
    “…The performance of the proposed approach is evaluated by comparing it with four population-based approaches and an existing hyper-heuristic approach named Hyper-Heuristic Scheduling Algorithm (HHSA). …”
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  5. 5
    PID-based control of a single-link flexible manipulator in vertical motion with genetic optimisation

    PID-based control of a single-link flexible manipulator in vertical motion with genetic optimisation by Md Zain, Badrul Aisham, Tokhi, M. Osman, Toha, Siti Fauziah

    Published 2009
    “…The important point is to evaluate the range of PID parameter which used in the GAs programmed to find the best value of this parameter. …”
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  6. 6
    Genetic algorithm for control and optimisation of exothermic batch process

    Genetic algorithm for control and optimisation of exothermic batch process by Tan, Min Keng

    Published 2013
    “…As such, another approach, GA is proposed to optimise the productivity without referring to a predetermined profile, namely genetic algorithm optimiser (GAO). …”
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  7. 7
    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
    “…The proposed algorithm underwent both qualitative and quantitative evaluations. …”
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  8. 8
    Application and evaluation of the evolutionary algorithms combined with conventional neural network to determine the building energy consumption of the residential sector

    Application and evaluation of the evolutionary algorithms combined with conventional neural network to determine the building energy consumption of the residential sector by Wang G., Mukhtar A., Moayedi H., Khalilpoor N., Tt Q.

    Published 2025
    “…The results of the evaluation demonstrated varying performances among the three evolutionary algorithms. …”
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  9. 9
    A Study of the Contribution of Nearest-Neighbour Thermodynamic Parameters to the DNA Sequences Generated by Ant Colony Optimisation

    A Study of the Contribution of Nearest-Neighbour Thermodynamic Parameters to the DNA Sequences Generated by Ant Colony Optimisation by Mohd Zaidi, Mohd Tumari, Zuwairie, Ibrahim, Kamarul Hawari, Ghazali, Faradila, Naim, Mohd Falfazli, Mat Jusof, Ismail, Ibrahim, Zulkifli, Md. Yusof, Kamal, Khalil, Muhammad Arif, Abdul Rahim, Sophan Wahyudi, Nawawi

    Published 2013
    “…The Watson-Crick base pair ∆Go37 was used as the distance between nodes for the thermodynamic parameters in the problem models for the heuristic approach in the ACS algorithms. …”
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  10. 10
    Analysis of the ECG signal using SVD-based parametric modelling technique

    Analysis of the ECG signal using SVD-based parametric modelling technique by Baali, Hamza, Salami, Momoh Jimoh Emiyoka, Akmeliawati, Rini, Aibinu, Abiodun Musa

    Published 2011
    “…A two-stage procedure is then used to estimate the EDS model parameters. Prony’s algorithm is first used to obtain initial estimates of the model, while the Gauss-Newton method is applied to solve the non-linear least-square optimisation problem. …”
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  11. 11
    Sensorless Adaptive Fuzzy Logic Control Of Permanent Magnet Synchronous Motor

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

    Published 2008
    “…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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  12. 12
    Modelling and calibration of high-pressure direct injection compressed natural gas engine

    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. …”
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  13. 13
    Evaluating Adan vs. Adam: an analysis of optimizer performance in deep learning

    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
    “…On the other hand, for image classification tasks, Adan provides more consistent optimisation across extended training periods. Based on these results, this paper aims to provide insights into the strengths and limitations of each optimizer, highlighting the importance of considering task-specific requirements when selecting an optimization algorithm for deep learning models.…”
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  14. 14
    Sediment load forecasting from a biomimetic optimization perspective: Firefly and Artificial Bee Colony algorithms empowered neural network modeling in �oruh River

    Sediment load forecasting from a biomimetic optimization perspective: Firefly and Artificial Bee Colony algorithms empowered neural network modeling in �oruh River by Katipo?lu O.M., Kartal V., Pande C.B.

    Published 2025
    “…4.457, and KGE = 0.737) compared to other models. Furthermore, the utilization of FA and ABC optimization techniques facilitated the optimization of the ANN model parameters. …”
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  15. 15
    Application of machine learning algorithms to predict removal efficiency in treating produced water via gas hydrate-based desalination

    Application of machine learning algorithms to predict removal efficiency in treating produced water via gas hydrate-based desalination by Nallakukkala, Sirisha, Tackie-Otoo, Bennet Nii, Aliyu, Ruwaida, Lal, Bhajan, Nallakukkala, Jagadish Ram Deepak, Devi, Gayathri

    Published 2025
    “…In this context. ML algorithms provide powerful data driven means to model complex relationship within experimental datasets to improve process optimisation This study systematically evaluated several supervised ML models, including Random Forest (RF) Support Vector Machines (SVM), Ridge Regression, Lasso Regression, Decision Tree, Extra Tree Regression, Gradient Boost, and XGBoost, to predict removal efficiency in GHBD system. …”
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  16. 16
    Control of an underactuated double-pendulum overhead crane using improved model reference command shaping: Design, simulation and experiment

    Control of an underactuated double-pendulum overhead crane using improved model reference command shaping: Design, simulation and experiment by Jaafar H.I., Mohamed Z., Ahmad M.A., Wahab N.A., Liyana Ramli, Shaheed M.H.

    Published 2024
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  17. 17
    PATCH-IQ: A Patch Based Learning Framework For Blind Image Quality Assessment

    PATCH-IQ: A Patch Based Learning Framework For Blind Image Quality Assessment by Abdul Manap, Redzuan, Ling, Shao, Frangi, Alejandro Federico

    Published 2017
    “…The regression algorithm is used to model human perceptual measures based on a training set of distorted images. …”
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  18. 18
    Optimal PI controller based PSO optimization for PV inverter using SPWM techniques

    Optimal PI controller based PSO optimization for PV inverter using SPWM techniques by Abdolrasol M.G.M., Hannan M.A., Hussain S.M.S., Ustun T.S.

    Published 2023
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  19. 19
    Hardware-in-the-loop study of a hybrid active force control scheme of an upper-limb exoskeleton for passive stroke rehabilitation

    Hardware-in-the-loop study of a hybrid active force control scheme of an upper-limb exoskeleton for passive stroke rehabilitation by Anwar, P. P. Abdul Majeed

    Published 2018
    “…A hardware-in-the-loop simulation is carried out to evaluate the appropriate gains of both the PD and the AFC inertial parameter gained that is tuned via the SKF algorithm. …”
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  20. 20
    Hardware-in-the-loop study of a hybrid active force control scheme of an upper-limb exoskeleton for passive stroke rehabilitation

    Hardware-in-the-loop study of a hybrid active force control scheme of an upper-limb exoskeleton for passive stroke rehabilitation by Anwar, P. P. Abdul Majeed

    Published 2018
    “…A hardware-in-the-loop simulation is carried out to evaluate the appropriate gains of both the PD and the AFC inertial parameter gained that is tuned via the SKF algorithm. …”
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