Search Results - (( parameter estimation using algorithm ) OR ( peer evaluation a algorithm ))

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  1. 1

    Using the evolutionary mating algorithm for optimizing deep learning parameters for battery state of charge estimation of electric vehicle by Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Nor Farizan, Zakaria, Mohd Mawardi, Saari

    Published 2023
    “…This paper presents the application of a recent metaheuristic algorithm namely Evolutionary Mating Algorithm (EMA) for optimizing the Deep Learning (DL) parameters to estimate the state of charge (SOC) of a battery for an electric vehicle in the real environment. …”
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    Article
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    Parameter estimation of cocomo model using the jaya algorithm for software cost estimation by Tan, Jie Chee

    Published 2019
    “…This thesis proposed the Jaya algorithm based on estimation of the software based on the COCOMO I model. …”
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    Undergraduates Project Papers
  4. 4

    Identifying and estimating solar cell parameters using an enhanced slime mould algorithm by Logeswaary, Devarajah, Mohd Ashraf, Ahmad, Jui, Julakha Jahan

    Published 2024
    “…The proposed ESMA was used to resolve the problem of estimating PV parameters based on the empirical current-voltage (I-V) data. …”
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    Article
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    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
    “…The influence of conventional genetic algorithm parameter - generation gap has been investigated too. …”
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    Article
  7. 7

    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
    “…In addition, the hyperparameter tuning problem is considered in this research to improve the developed hybrid model by using the AOA algorithm. Lastly, a new hybrid technique suggests tackling the current image encryption application problem by using the estimated parameters of chaotic systems with an optimization algorithm, the SKF algorithm. …”
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    Thesis
  8. 8

    Comparison of machine learning algorithms for estimating mangrove age using sentinel 2A at Pulau Tuba, Kedah, Malaysia / Fareena Faris Francis Singaram by Faris Francis Singaram, Fareena

    Published 2021
    “…Therefore, this study aimed to used OBIA method with selected machine learning algorithm to estimate the mangrove age by using Sentinel 2A image. …”
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    Thesis
  9. 9

    Estimation of photovoltaic models using an enhanced Henry gas solubility optimization algorithm with first-order adaptive damping Berndt-Hall-Hall-Hausman method by Ramachandran, Murugan, Sundaram, Arunachalam, Ridha, Hussein Mohammed, Mirjalili, Seyedali

    Published 2024
    “…Then in terms of methodology, the Enhanced Henry Gas Solubility Optimization (EHGSO) algorithm is combined with the Sine-Cosine mutualism phase of Symbiotic Organisms Search (SOS) for efficiently estimating the unknown parameters of PV models. …”
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    Article
  10. 10

    Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh by Rawaa Dawoud Hassan, Al-Dabbagh

    Published 2015
    “…ARDE algorithm makes use of JADE strategy and the MDE_pBX parameters adaptive schemes as frameworks. …”
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    Thesis
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    Evaluating power efficient algorithms for efficiency and carbon emissions in cloud data centers: a review by Uddin, Mueen, Darabidarabkhani, Yasaman, Shah, Asadullah, Memon, Jamshed

    Published 2015
    “…The three algorithms are evaluated for performance using three parameters; power efficiency, cost effectiveness, and amount of CO2 emissions. …”
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    Article
  14. 14

    Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence by S. S. S. , Ranjit

    Published 2011
    “…Based on the theoretical and fundamental research analysis the FUHS16 and UHDS16 algorithms using 16 × 16 block-based motion estimation formulations were developed. …”
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    Book Chapter
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    Kalman filter based impedance parameter estimation for transmission line and distribution line by Siti Nur Aishah, Mohd Amin

    Published 2019
    “…The positive sequence measurement is use to estimate the positive sequence parameters which will generate inaccurate parameter estimates. …”
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    Thesis
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    Model selection approaches of water quality index data by Kamarudin, Nur Azulia, Ismail, Suzilah

    Published 2016
    “…Automatic model selection by using algorithm can avoid huge variability in model specification process compared to manual selection.With the employment of algorithm, the right model selected is then also used for forecasting purposes. …”
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    Article
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    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
    “…This work proposes a novel approach to chew count estimation using particle swarm optimization (PSO) combined with a peak detection algorithm. …”
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    Article
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    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
    “…This work proposes a novel approach to chew count estimation using particle swarm optimization (PSO) combined with a peak detection algorithm. …”
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    Article
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    Multi-Agent cubature Kalman optimizer: A novel metaheuristic algorithm for solving numerical optimization problems by Zulkifli, Musa, Zuwairie, Ibrahim, Mohd Ibrahim, Shapiai

    Published 2024
    “…CTT can use small values for parameters P(0), Q, and R, so CKF was developed to overcome KF and other estimation algorithms. …”
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    Article
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    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 HMVOSCA algorithm is used to tune the linear and nonlinear parameters to reduce the gap between the estimated results and the actual results. …”
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    Conference or Workshop Item