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  1. 1
    Design and development of prototype robot gripper for object weight measurement

    Design and development of prototype robot gripper for object weight measurement by Almassri, Ahmed M. M.

    Published 2014
    “…Therefore, this study has proposed a robotic gripper prototype with a new configuration of pressure sensor distribution, based on development of grasping algorithm for object’s weight measurement. …”
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  2. 2
    Realization of microcontroller-based polarization control system with genetic algorithm

    Realization of microcontroller-based polarization control system with genetic algorithm by Mamdoohi, Ghazaleh, Esmaeilian-Marnani, Aida, Abas, Ahmad Fauzi, Samsudin, Khairulmizam, Hidayat, Ariya, Ibrahim, Noor Hisham, Mahdi, Mohd Adzir

    Published 2009
    “…To reach optimum performance, the code is optimized by using the best genetic parameter to achieve the fastest execution time. This algorithm consumes low size of memory besides providing fast speed. …”
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  3. 3
    Parameter-Less Simulated Kalman Filter

    Parameter-Less Simulated Kalman Filter by Nor Hidayati, Abdul Aziz, Zuwairie, Ibrahim, Nor Azlina, Ab. Aziz, Saifudin, Razali

    Published 2017
    “…Further studies on the effect of P(0), Q and R values suggest that the SKF algorithm can be realized as a parameter-less algorithm. …”
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  4. 4
    Enhancing solid oxide fuel cell efficiency through advanced model identification using differential evolutionary mutation fennec fox algorithm

    Enhancing solid oxide fuel cell efficiency through advanced model identification using differential evolutionary mutation fennec fox algorithm by Singla, Manish Kumar, Gupta, Jyoti, Kumar, Ramesh, Jangir, Pradeep, Louzazni, Mohamed, Giri, Nimay Chandra, Al Gburi, Ahmed Jamal Abdullah, EI‑Kenawy, E. I.‑Sayed M., Alharbi, Amal H.

    Published 2025
    “…The computational time of the proposed algorithm is 1.001 s, followed by the parent algorithm FFA (1.199 s) and some of the compared algorithms. …”
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  5. 5
    LS-SVM Hyper-parameters Optimization Based on GWO Algorithm for Time Series Forecasting

    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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  6. 6
    Optimization of turning parameters using genetic algorithm method

    Optimization of turning parameters using genetic algorithm method by Shah Izwandi, Mohd Zawawi

    Published 2008
    “…This study about development of optimization for turning parameters based on the Genetic Algorithm (GA). This method was demonstrated for the optimization of machining parameters for turning operation using conventional lathe machines. …”
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  7. 7
    Topological Clustering via Adaptive Resonance Theory With Information Theoretic Learning

    Topological Clustering via Adaptive Resonance Theory With Information Theoretic Learning by Masuyama, Naoki, Loo, Chu Kiong, Ishibuchi, Hisao, Kubota, Naoyuki, Nojima, Yusuke, Liu, Yiping

    Published 2019
    “…In contrast, the proposed algorithm realizes a stable computation and reduces the number of parameters compared to existing algorithms. …”
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  8. 8
    A Study of Ikaz and Normalized Hilbert transform for solving faulty in pipeline distribution system using transmission line modelling

    A Study of Ikaz and Normalized Hilbert transform for solving faulty in pipeline distribution system using transmission line modelling by Hanafi, M. Yusop, M. F., Ghazali, Azmi, W. H., Mohd Fadhlan, Mohd Yusof, M. A., Pi Remli, M. A. A., Rahim

    Published 2019
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  9. 9
    Enhanced artificial bee colony-least squares support vector machines algorithm for time series prediction

    Enhanced artificial bee colony-least squares support vector machines algorithm for time series prediction by Zuriani, Mustaffa

    Published 2014
    “…The combination of lvABC and cmABC algorithm, which is later introduced as Enhanced Artificial Bee Colony–Least Squares Support Vector Machine (eABC-LSSVM), is realized in prediction of non renewable natural resources commodity price. …”
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  10. 10
    Rice Predictive Analysis Mechanism Utilizing Grey Wolf Optimizer-Least Squares Support Vector Machines

    Rice Predictive Analysis Mechanism Utilizing Grey Wolf Optimizer-Least Squares Support Vector Machines by Zuriani, Mustaffa, M. H., Sulaiman

    Published 2015
    “…In this regard, this study proposes a hybridization of LSSVM with a new Swarm Intelligence (SI) algorithm namely, Grey Wolf Optimizer (GWO). With such hybridization, the hyper-parameters of interest are automatically optimized by the GWO. …”
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  11. 11
    Dengue outbreak prediction: hybrid meta-heuristic model

    Dengue outbreak prediction: hybrid meta-heuristic model by Zuriani, Mustaffa, Mohd Herwan, Sulaiman, Ernawan, Ferda, Yuhanis, Yusof, Mohamad Farhan, Mohamad Mohsin

    Published 2018
    “…Here, the FPA is served as an optimization algorithm for LSSVM. The hybrid FPA-LSSVM is later realized for prediction of dengue outbreak in Yogyakarta, Indonesia. …”
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  12. 12
    Improving PID controller of motor shaft angular position by using genetic algorithm

    Improving PID controller of motor shaft angular position by using genetic algorithm by Muhamad, Arif Abidin

    Published 2015
    “…This study represents Genetic Algorithm optimization of PID parameters gain in model reference robust control system structure for desired position of incremental servomotor. …”
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  13. 13
    Reduced Fuzzy Recursive Least-Squares Algorithm For Real Time Estimation

    Reduced Fuzzy Recursive Least-Squares Algorithm For Real Time Estimation by Cheah, Kah Wai

    Published 2018
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  14. 14
    Application of LSSVM by ABC in energy commodity price forecasting

    Application of LSSVM by ABC in energy commodity price forecasting by Mustaffa, Zuriani, Yusof, Yuhanis, Kamaruddin, Siti Sakira

    Published 2014
    “…The importance of the hyper parameters selection for a kernel-based algorithm, viz.Least Squares Support Vector Machines (LSSVM) has been a critical concern in literature.In order to meet the requirement, this work utilizes a variant of Artificial Bee Colony (known as mABC) for hyper parameters selection of LSSVM.The mABC contributes in the exploitation process of the artificial bees and is based on Levy mutation.Realized in crude oil price forecasting, the performance of mABC-LSSVM is guided based on Mean Absolute Percentage Error (MAPE) and Root Mean Square Error (RMSPE) and compared against the standard ABC-LSSVM and LSSVM optimized by Genetic Algorithm. …”
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  15. 15
    High performance visualization of human tumor growth software

    High performance visualization of human tumor growth software by Alias, Norma, Mohd. Said, Norfarizan, Khalid, Siti Nur Hidayah, Sin, Dolly Tien Ching, Phang, Tau Ing

    Published 2008
    “…The platform for high performance computing of the parallel algorithms run on a distributed parallel computer system. …”
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  16. 16
    Exploration of ikaz and normalized hilbert transform for solving faulty in pipeline distribution system using transmission line modelling

    Exploration of ikaz and normalized hilbert transform for solving faulty in pipeline distribution system using transmission line modelling by Hanafi, M. Yusop, M. F., Ghazali, W. H., Azmi, M. F. M., Yusof, M. A., PiRemli, M. A., A. Rahim

    Published 2018
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  17. 17
    Probabilistic ensemble fuzzy ARTMAP optimization using hierarchical parallel genetic algorithms

    Probabilistic ensemble fuzzy ARTMAP optimization using hierarchical parallel genetic algorithms by Loo, C.K., Liew, W.S., Seera, M., Lim, Einly

    Published 2015
    “…The issues addressed are the sequence of training data for supervised learning and optimum parameter tuning for parameters such as baseline vigilance. …”
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  18. 18
    The effect of fuel injection equipment on the dispersed phase of water-in-diesel emulsions

    The effect of fuel injection equipment on the dispersed phase of water-in-diesel emulsions by Ismael, M.A., Heikal, M.R., Aziz, A.R.A., Syah, F., Zainal A., E.Z., Crua, C.

    Published 2018
    “…To address this issue we sampled an emulsion at several locations within the injection system, from the fuel tank to the injector nozzle, and measured the evolution of the droplet size distribution of the emulsion's dispersed phase. We varied the water mass fraction (5, 10 and 15 by volume) of the emulsion and the injection pressure (500, 1000 and 1500 bar), imaged the samples using a high-resolution microscope and extracted the droplet size distribution using a purpose-built image processing algorithm. …”
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  19. 19
    The effect of fuel injection equipment on the dispersed phase of water-in-diesel emulsions

    The effect of fuel injection equipment on the dispersed phase of water-in-diesel emulsions by Ismael, M.A., Heikal, M.R., Aziz, A.R.A., Syah, F., Zainal A., E.Z., Crua, C.

    Published 2018
    “…To address this issue we sampled an emulsion at several locations within the injection system, from the fuel tank to the injector nozzle, and measured the evolution of the droplet size distribution of the emulsion's dispersed phase. We varied the water mass fraction (5, 10 and 15 by volume) of the emulsion and the injection pressure (500, 1000 and 1500 bar), imaged the samples using a high-resolution microscope and extracted the droplet size distribution using a purpose-built image processing algorithm. …”
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  20. 20
    Metaheuristic optimization of perovskite solar cell using hybrid L₃₂ Taguchi DoE-based genetic algorithm

    Metaheuristic optimization of perovskite solar cell using hybrid L₃₂ Taguchi DoE-based genetic algorithm by Salehuddin, Fauziyah, Ahmad Jalaludin, Nabilah, Kaharudin, Khairil Ezwan, Arith, Faiz, Mohd Zain, Anis Suhaila, Md Junos@Yunus, Siti Aisah, R Apte, Prakash

    Published 2024
    “…This paper emphasizes the metaheuristic optimization approach in searching for the optimum input parameters of perovskite solar cell (PSC). The proposed approach is realized using Solar Cell Capacitance Simulator (SCAPS-1D) software incorporated with a hybrid L32 Taguchi DoE-based Genetic Algorithm. …”
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