Search Results - (( rendering optimization based algorithm ) OR ( basic optimization mead algorithm ))

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  1. 1
    Optimizing the SEIRD model for COVID-19 in Malaysia using pymoo framework

    Optimizing the SEIRD model for COVID-19 in Malaysia using pymoo framework by Abdul Hadi, Muhammad Salihi, Amran, Muhammad Aiman Haziqh, Zulkarnain, Norsyahidah

    Published 2025
    “…However, the introduction of time-dependent coefficients in both models increases the number of optimization variables. To solve this, the Nelder-Mead and Pattern Search algorithms were recommended. …”
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  2. 2
    Dynamic Economic Dispatch For Large Scale Power Systems: A Lagrangian Relaxation Approach

    Dynamic Economic Dispatch For Large Scale Power Systems: A Lagrangian Relaxation Approach by Ab Ghani, Mohd Ruddin, Hindi, K. S.

    Published 1991
    “…Otherwise, Dantzig-Wolfe decomposition is invoked, using almost all the information generated during subgradient optimization to ensure a speedy conclusion. The computational efficiency of the algorithm renders it suitable for on-line dispatch.…”
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  3. 3
    Using predictive analytics to solve a newsvendor problem / S. Sarifah Radiah Shariff and Hady Hud

    Using predictive analytics to solve a newsvendor problem / S. Sarifah Radiah Shariff and Hady Hud by Shariff, S. Sarifah Radiah, Hud, Hady

    Published 2023
    “…The pandemic has resulted in unpredictable customers’ purchasing patterns post-pandemic has rendered heuristic-based forecasting large forecast errors, which leads to poor decision-making. …”
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  4. 4
    Predictive analysis of dengue outbreak based on an improved salp swarm algorithm

    Predictive analysis of dengue outbreak based on an improved salp swarm algorithm by Zuriani, Mustaffa, M. H., Sulaiman, Khairunnisa Amalina, Mohd Rosli, Mohamad Farhan, Mohamad Mohsin, Yuhanis, Yusof

    Published 2020
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  5. 5
    Integration of simulation for ergonomics assessment in operation control centre (railway industries) / Adib Zulfadhli Mohd Alias

    Integration of simulation for ergonomics assessment in operation control centre (railway industries) / Adib Zulfadhli Mohd Alias by Adib Zulfadhli, Mohd Alias

    Published 2019
    “…This study will focus on the translation of the CAD/Revit model into simulation software, either directly or through the intermediate stage of rendering package. Complete CAD/Revit model can be used to generate simulation model by straight forward translation of the whole model or with the algorithms for optimization. …”
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  6. 6
    WHALE OPTIMIZATION NEURAL NETWORK FOR DAILY WATER LEVEL FORECASTING CONSIDERING THE CHANGING CLIMATE

    WHALE OPTIMIZATION NEURAL NETWORK FOR DAILY WATER LEVEL FORECASTING CONSIDERING THE CHANGING CLIMATE by Kuok, King Kuok, Chiu, Po Chan, Md. Rezaur, Rahman, Teng, Yeow Haur

    Published 2024
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  7. 7
    Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm

    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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  8. 8
    Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm

    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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  9. 9
    Evaluating the Efficacy of Intelligent Methods for Maximum Power Point Tracking in Wind Energy Harvesting Systems

    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
    “…Furtherly, Artificial Intelligence (AI)-based MPPT algorithms were proposed for the WEHS as either standalone or integrated with the traditional MPPT methods. …”
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  10. 10
    Development of intelligent evaluation system for product end-of-life selection strategy

    Development of intelligent evaluation system for product end-of-life selection strategy by Zakri, Ghazalli

    Published 2011
    “…This study integrates the travelling salesman problem with genetic algorithm (TSP-GA) for finding the optimal disassembly sequence and disassembling the EOL product. …”
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  11. 11
    Multivariable optimization of carbon nanoparticles synthesized from waste facial tissues by artificial neural networks, new material for downstream quenching of quantum dots

    Multivariable optimization of carbon nanoparticles synthesized from waste facial tissues by artificial neural networks, new material for downstream quenching of quantum dots by Shojaei, Taha Roodbar, Mohd Salleh, Mohamad Amran, Mobli, Hossein, Aghbashlo, Mortaza, Tabatabaei, Meisam

    Published 2019
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  12. 12
    Augmented Reality Framework For Symbian Mobile Devices

    Augmented Reality Framework For Symbian Mobile Devices by Oui, Wei Wei

    Published 2013
    “…Open source libraries such as OpenGL and OpenCV are used to develop mobile AR framework. Optimized algorithms are used to ensure that AR application running smooth. …”
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  13. 13
    Intelligent traffic lights using Q-learning

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

    Published 2022
    “…Q-learning derives benefits from past experiences and determines the optimal course of action based on them. The performance of the proposed system has been measured against that of the traditional system, which is a fixed time cycle system. …”
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  14. 14
    Cuckoo optimised 2DOF controllers for stabilising the frequency changes in restructured power system with wind-hydro units

    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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  15. 15
    Automated fault detection and extraction under gas chimneys using hybrid discontinuity attributes

    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
    “…3D-seismic data have increasingly shifted seismic interpretation work from a horizons-based to a volume-based focus over the past decade. …”
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  16. 16
    Hybrid dynamic scheduling model for flexible manufacturing system with machine availability and new job arrivals

    Hybrid dynamic scheduling model for flexible manufacturing system with machine availability and new job arrivals by Paslar, Shahla

    Published 2015
    “…The idea of hybridizing the newly developed biogeography based optimization algorithm (BBO) with variable neighborhood structure (VNS) is proposed in order to produce a high performance initial schedule in terms of minimum completion time, tardiness and flow time within reasonable amount of time. …”
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  17. 17
    Personalized one-shot local adaptation federated learning for mortality prediction in multi-center Intensive Care Unit

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

    Published 2024
    “…Step 2 enables highly personalized models as students to rebalance global and local data knowledge through knowledge distillation optimizations. Step 3 automatically evolves the best-fitting parameters for the highly personalized model at each center using an adapted genetic algorithm. …”
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