Search Results - (( rendering optimization based algorithm ) OR ( using optimization model algorithm ))

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  1. 1

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

    Published 1991
    “…The solution algorithm is based on Lagrangian relaxation and on exploiting the intimate relationship between optimizing the dual Lagrangian function and Dantzig-Wolfe decomposition. …”
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    Article
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    Integration of simulation for ergonomics assessment in operation control centre (railway industries) / Adib Zulfadhli Mohd Alias by Adib Zulfadhli, Mohd Alias

    Published 2019
    “…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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    Thesis
  4. 4

    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 unpredictability of customers’ purchasing patterns postpandemic has rendered heuristic-based forecasting large forecast errors. …”
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    Book Section
  5. 5

    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
    “…These methods present an effective alternative that treats plants as black-box systems without requiring explicit models. The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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  6. 6

    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
    “…These methods present an effective alternative that treats plants as black-box systems without requiring explicit models. The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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  8. 8

    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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    Thesis
  9. 9

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

    Published 2024
    “…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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    Thesis
  10. 10

    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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  11. 11

    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
    “…Contrary to several available fault tracking techniques that use local seismic continuity like coherency attributes, our hybrid method is based on directed semblance, which incorporates aspects of Dave Haleâ��s superior fault-oriented semblance algorithm. …”
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  12. 12

    Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems by Kek, Sie Long

    Published 2011
    “…Instead of solving the original optimal control problem, the model-based optimal control problem is solved. …”
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    Optimization of modified Bouc–Wen model for magnetorheological damper using modified cuckoo search algorithm by Rosmazi, Rosli, Zamri, Mohamed

    Published 2021
    “…This article presents a new modified cuckoo search algorithm with dynamic discovery probability and step-size factor for optimizing the Bouc–Wen Model in magnetorheological damper application. …”
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    Article
  16. 16

    Application of conjugate gradient approach for nonlinear optimal control problem with model-reality differences by Leong, Wah June, Sie, Long Kek, Teo, Kok Lay, Sim, Sy Yi

    Published 2018
    “…In our approach, the linear quadratic optimal control model, which is adding the adjusted parameters into the model used, is employed. …”
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  17. 17

    Optimization of multipurpose reservoir operation using evolutionary algorithms / Mohammed Heydari by Mohammed , Heydari

    Published 2017
    “…An improved particle swarm algorithm (HPSOGA) is used to solve complex problems of water resources optimization. …”
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    Thesis
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    Modeling and optimization of multi-holes drilling path using Particle Swarm Optimization by Ab Rashid, Mohd Fadzil Faisae, Nik Mohamed, Nik Mohd Zuki, Romlay, Fadhlur Rahman Mohd, Razali, Akhtar Razul, Asmizam, Mokhtar

    Published 2018
    “…Later the problem is optimized using Particle Swarm Optimization (PSO) and compared with other algorithms including the new metaheuristics algorithms. …”
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    Research Report
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    Application of conjugate gradient approach for nonlinear optimal control problem with model-reality difference by Sie, Long Kek, Wah, June Leong, Sy, Yi Sim, Kok, Lay Teo

    Published 2018
    “…In our approach, the linear quadratic optimal control model, which is adding the adjusted parameters into the model used, is employed. …”
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    Article
  20. 20

    Nonlinear auto-regressive model structure selection using binary particle swarm optimization algorithm / Ahmad Ihsan Mohd Yassin by Mohd Yassin, Ahmad Ihsan

    Published 2014
    “…This thesis proposes the application of a stochastic optimization algorithm called Binary Particle Swarm Optimization algorithm for structure selection of polynomial NARX/NARMA/NARMAX models. …”
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    Thesis