Search Results - (( parameter optimization means algorithm ) OR ( parameters evaluation method algorithm ))

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  1. 1

    Impact of evolutionary algorithm on optimization of nonconventional machining process parameters by B V, Raghavendra, R Annigiri, Anandkumar, Srikatamurthy, JS

    Published 2025
    “…Using a Python environment, three evolutionary algorithms such as, Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Firefly Algorithm (FA), were simulated to evaluate their effectiveness in minimizing surface roughness (Ra). …”
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    Article
  2. 2

    Analysis of toothbrush rig parameter estimation using different model orders in Real-Coded Genetic Algorithm (RCGA) by Ainul, H. M. Y., Salleh, S. M., Halib, N., Taib, H., Fathi, M. S.

    Published 2018
    “…Realcoded genetic algorithm (RCGA) as a stochastic global search method was applied for optimization. …”
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    Article
  3. 3

    Modeling time series data using Genetic Algorithm based on Backpropagation Neural network by Haviluddin

    Published 2018
    “…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. …”
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    Thesis
  4. 4

    Improved stochastic gradient descent algorithm with mean-gradient adaptive stepsize for solving large-scale optimization problems by Zulkifli, Munierah, Abd Rahmin, Nor Aliza, Wah, June Leong

    Published 2023
    “…Stochastic gradient descent (SGD) is one of the most common algorithms used in solving large unconstrained optimization problems. …”
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    Article
  5. 5

    A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

    Published 2023
    “…The research starts with developing the hybrid deep learning model consisting of DNN and a K-Means Clustering Algorithm. Then, the developed algorithm is implemented to estimate the parameters of the Lorenz system. …”
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  6. 6

    Analysis of Toothbrush Rig Parameter Estimation Using Different Model Orders in Real Coded Genetic Algorithm (RCGA) by Ainul, H. M. Y., Salleh, S. M., Halib, N., Taib, H., Fathi, M. S.

    Published 2024
    “…Real-coded genetic algorithm (RCGA) as a stochastic global search method was applied for optimization. …”
    Article
  7. 7

    Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm by Manoharan P., Ravichandran S., Kavitha S., Tengku Hashim T.J., Alsoud A.R., Sin T.C.

    Published 2025
    “…The orthogonal learning mechanism improves the performance of the original GOOSE algorithm. This FC model uses the root mean squared error as the objective function for optimizing the unknown parameters. …”
    Article
  8. 8

    Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems by Nor Sakinah, Abdul Shukor

    Published 2019
    “…Notably, the SPSA and GSPSA based methods only produced the optimal design parameter at the final iteration while it may keep a better design parameter during the tuning process if it has a memory feature. …”
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    Thesis
  9. 9

    Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems by Nor Sakinah, Abdul Shukor

    Published 2019
    “…Notably, the SPSA and GSPSA based methods only produced the optimal design parameter at the final iteration while it may keep a better design parameter during the tuning process if it has a memory feature. …”
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    Thesis
  10. 10

    Novel chewing cycle approach for peak detection algorithm of chew count estimation by Selamat, Nur Asmiza, Md Ali, Sawal Hamid, Ismail, Ahmad Ghadafi, Ahmad, Siti Anom, Minhad, Khairun Nisa'

    Published 2025
    “…The chewing dataset comprises signals collected from 20 participants consuming eight different food types, with proximity sensors (PSs) detecting temporalis muscle activity. The peak detection algorithm identifies key signal features, while PSO optimizes the peak prominence and width parameters to minimize the mean absolute error (MAE) in chew count estimation. …”
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    Article
  11. 11

    Novel chewing cycle approach for peak detection algorithm of chew count estimation by Selamat, Nur Asmiza, Md Ali, Sawal Hamid, Ismail, Ahmad Ghadafi, Ahmad, Siti Anom, Minhad, Khairun Nisa’

    Published 2025
    “…The chewing dataset comprises signals collected from 20 participants consuming eight different food types, with proximity sensors (PSs) detecting temporalis muscle activity. The peak detection algorithm identifies key signal features, while PSO optimizes the peak prominence and width parameters to minimize the mean absolute error (MAE) in chew count estimation. …”
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    Article
  12. 12

    Modified multi-verse optimizer for nonlinear system identification of a double pendulum overhead crane by Julakha, Jahan Jui, Mohd Ashraf, Ahmad, Muhammad Ikram, Mohd Rashid

    Published 2021
    “…The efficiency of the proposed HMVOSCA algorithm is evaluated using the convergence curve, parameter estimation error, bode plot, function plot, and Wilcoxon's test method. …”
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  13. 13

    VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern by Angeline Teoh, Szu Fern

    Published 2012
    “…These two models are based on topological placement method. DM is optimized using genetic algorithm (GA). …”
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  14. 14

    An intelligent voltage controller for a PV inverter system using simulated annealing algorithm-based PI tuning approach by Najeeb M., Razali R., Daniyal H., Mahmood A., Mansor M.

    Published 2023
    “…Besides, it is then used to optimize the PI parameters in order to get the desired output voltage of the PV electrical inverter along with the PWM method. …”
    Article
  15. 15

    Zero root-mean-square error for single- and double-diode photovoltaic models parameter determination by Mohammed Ridha, Hussein, Hizam, Hashim, Mirjalili, Seyedali, Othman, Mohammad Lutfi, Ya’acob, Mohammad Effendy

    Published 2022
    “…This may be extremely helpful both practically and theoretically in the PV system simulation, optimization, and evaluation. Numerous stochastic methods have been widely utilized in recent decades to tackle the parameter extraction optimization problem. …”
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    Article
  16. 16

    Machine learning methods for herschel-bulkley fluids in annulus: Pressure drop predictions and algorithm performance evaluation by Kumar, A., Ridha, S., Ganet, T., Vasant, P., Ilyas, S.U.

    Published 2020
    “…The impact of each input parameter affecting the pressure drop is quantified using the RF algorithm. …”
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    Article
  17. 17

    Modeling and Analysis of New Hybrid Clustering Technique for Vehicular Ad Hoc Network by Abdulrazzak H.N., Hock G.C., Mohamed Radzi N.A., Tan N.M.L., Kwong C.F.

    Published 2023
    “…To address these problems, a novel method combining a covering rough set and a K-Means clustering algorithm (RK-Means) was proposed in this paper. …”
    Article
  18. 18

    An Intelligent Voltage Controller for a PV Inverter System Using Simulated Annealing Algorithm-Based PI Tuning Approach by Najeeb, Mushtaq, Muhamad, Mansor, Ramdan, Razali, Hamdan, Daniyal, Ali, Mahmood

    Published 2017
    “…Besides, it is then used to optimize the PI parameters in order to get the desired output voltage of the PV electrical inverter along with the PWM method. …”
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    Article
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    Fuzzy clustering method and evaluation based on multi criteria decision making technique by Sameer, Fadhaa Othman

    Published 2018
    “…This proposed algorithm is developed based on heuristic method named modified binary particle swarm optimization (MBPSO) with kernel fuzzy clustering method as a fitness function. …”
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    Thesis