Search Results - (( (wandering OR rendering) optimization method algorithm ) OR ( java implication new algorithm ))

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  1. 1

    Mussels wandering optimization algorithmn based training of artificial neural networks for pattern classification by Abusnaina, Ahmed A., Abdullah, Rosni

    Published 2013
    “…Traditional training algorithms have some drawbacks such as local minima and its slowness.Therefore, evolutionary algorithms are utilized to train neural networks to overcome these issues.This research tackles the ANN training by adapting Mussels Wandering Optimization (MWO) algorithm.The proposed method tested and verified by training an ANN with well-known benchmarking problems.Two criteria used to evaluate the proposed method were overall training time and classification accuracy.The obtained results indicate that MWO algorithm is on par or better in terms of classification accuracy and convergence training time.…”
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    Conference or Workshop Item
  2. 2

    Adapting and enhancing mussels wandering optimization algorithm for supervised training of neural networks by Abusnaina, Ahmed A. A.

    Published 2015
    “…In addition, training NN is still highly-time consuming. The Mussels Wandering Optimization (MWO) is a recent metaheuristic optimization algorithm inspired ecologically by mussels movement behavior. …”
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    Thesis
  3. 3

    Optimization Of 3d Reconstruction Surface Rendering Algorithm For Osferion Bone Void Filling by Chin, Daniel Jie Yuan

    Published 2023
    “…Among the 3D reconstruction algorithms, surface rendering algorithms are more suitable for effectively visualizing the bones’ structure and shape. …”
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  6. 6

    Success history moth flow optimization for multi-goal generation dispatching with nonlinear cost functions by Alam, Mohammad Khurshed, Mohd Herwan, Sulaiman, Sayem, Md. Shaoran, Ringku, Md Mahfuzer Akter, Imtiaz, Shahriar, Khan, Rahat

    Published 2023
    “…The valve-point loading causes oscillations in the input-output characteristics of generating units, hence rendering the CEED problem an imperfect optimization problem. …”
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  7. 7

    Evaluating the Efficacy of Intelligent Methods for Maximum Power Point Tracking in Wind Energy Harvesting Systems by Umar D.A., Alkawsi G., Jailani N.L.M., Alomari M.A., Baashar Y., Alkahtani A.A., Capretz L.F., Tiong S.K.

    Published 2024
    “…These traditional methods in the standalone form are characterized by some drawbacks which render the method ineffective. …”
    Review
  8. 8

    Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm by Shahrizal, Saat, Mohd Ashraf, Ahmad, Mohd Riduwan, Ghazali

    Published 2025
    “…The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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    Article
  9. 9

    Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm by Shahrizal, Saat, Mohd Ashraf, Ahmad, Mohd Riduwan, Ghazali

    Published 2025
    “…The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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    Article
  10. 10

    Performance of 2-DOF PID controller in AGC of two area interconnected power system using PSO algorithm by Peddakapu, Kurukuri, Mohd Rusllim, Mohamed, Srinivasarao, P., Kishore, Dokala Janandra Krishna, Koteswararao, D.A., Swamy, P. S.P.R.

    Published 2022
    “…Therefore, in this work, particle swarm optimization (PSO) algorithm is formulated for tuning the gain values of the suggested controllers in multi-area interconnected system. …”
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  11. 11

    Cuckoo optimised 2DOF controllers for stabilising the frequency changes in restructured power system with wind-hydro units by Peddakapu, K., M. R., Mohamed, M. H., Sulaiman, Srinivasarao, P., Kishore, D. J. K., P. K., Leung

    Published 2021
    “…Different types of metaheuristic optimisation methods like teaching–learning-based optimisation (TLBO) and cuckoo search algorithms are suggested to acquire the optimal gain values of the proposed controllers. …”
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    Article
  12. 12

    Intelligent traffic lights using Q-learning by Mohd Yusop, Muhammad Aminuddin, Mansor, Hasmah, Gunawan, Teddy Surya, Nasir, Haidawati,

    Published 2022
    “…The conventional traffic light system contributes to the safety of the road but is not an effective method of traffic control. The failure of traffic intersections to learn from their past mistakes has rendered them incapable of adapting to the dynamic changes in traffic flow. …”
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    Proceeding Paper
  13. 13

    Personalized one-shot local adaptation federated learning for mortality prediction in multi-center Intensive Care Unit by Deng, Ting

    Published 2024
    “…After conducting stepwise experiments and comparing with three benchmark methods - a baseline FL method and two PFL approaches in similar optimization scheme - the results shows that POLA not only systematically optimizes its internal outputs but also outperforms the comparison methods. …”
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    Electrocardiogram based heart disease diagnosis using artificial intelligence by Hussain Kareem, Khleaf

    Published 2015
    “…Accordingly, the first step is an image segmentation method using proposed thresholding algorithms has been used to locate objects and boundaries of the ECG signal and background grid lines in the ECG images. …”
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  16. 16

    Automated fault detection and extraction under gas chimneys using hybrid discontinuity attributes by Imran, Q.S., Siddiqui, N.A., Latiff, A.H.A., Bashir, Y., Khan, M., Qureshi, K., Al-Masgari, A.A.-S., Ahmed, N., Jamil, M.

    Published 2021
    “…The data optimization and conditioning processes are applied to suppress random and coherent noise first, and then a combination of seismic attributes is generated and co-rendered to enhance the discontinuities. …”
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    Article