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  1. 1
    Optimization of earthquake energy dissipation system by genetic algorithm

    Optimization of earthquake energy dissipation system by genetic algorithm by Hejazi, Farzad, Toloue, Iraj, Jaafar, Mohd Saleh, Noorzaie, Jamaloddin

    Published 2013
    “…However, the available literature on optimizing earthquake energy dissipation systems shows that most researchers have considered optimization processes using just one or a few parameters applicable only to simple SDOF or MDOF systems. …”
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  2. 2
    Single Machine Connected Infinite Bus system tuning coordination control using biogeography-based optimization algorithm

    Single Machine Connected Infinite Bus system tuning coordination control using biogeography-based optimization algorithm by Kasilingam G., Pasupuleti J., Bharatiraja C., Adedayo Y.

    Published 2023
    “…The objective function J is framed using Integral square error (ISE) and the optimal parameters can be obtained by minimizing the objective function using the proposed Biogeography Based Optimization (BBO) algorithm. …”
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  3. 3
    Eccentricity Optimization of NGB System by using Multi-Objective Genetic Algorithm

    Eccentricity Optimization of NGB System by using Multi-Objective Genetic Algorithm by Yazdi, H.M., Ramli Sulong, N.H.

    Published 2009
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  4. 4
    Optimization of Off-Centre bracing system using Genetic Algorithm

    Optimization of Off-Centre bracing system using Genetic Algorithm by Yazdi, H.A. Mosalman, Ramli Sulong, Nor Hafizah

    Published 2011
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  5. 5
    A memory-guided Jaya algorithm to solve multi-objective optimal power flow integrating renewable energy sources

    A memory-guided Jaya algorithm to solve multi-objective optimal power flow integrating renewable energy sources by Ahmadipour M., Ali Z., Ramachandaramurthy V.K., Ridha H.M.

    Published 2025
    “…A smart memory-based strategy is incorporated into the algorithm to enhance solution optimality, convergence properties, and exploitation capabilities. …”
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  6. 6
    Adaptive model predictive control based on wavelet network and online sequential extreme learning machine for nonlinear systems

    Adaptive model predictive control based on wavelet network and online sequential extreme learning machine for nonlinear systems by Salih, Dhiadeen Mohammed

    Published 2015
    “…This allowed also learning unmodeled or time-varying dynamics of the system and enhancing the modeling accuracy. An analytical analysis based on ELM theories presented to prove the capability of the LWN to support the OSELM algorithm (LWN-OSELM). …”
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  7. 7
    A New Approach of Optimal Search Solution in Particle Swarm Optimization (PSO) Algorithm for Object Detection Method

    A New Approach of Optimal Search Solution in Particle Swarm Optimization (PSO) Algorithm for Object Detection Method by Zalili, Musa, Mohd Hafiz, Mohd Hassin, Nurul Izzatie Husna, Fauzi, Rohani, Abu Bakar, Watada, Junzo

    Published 2018
    “…Furthermore, the process of detected an object in every frame is time consuming as the entire frame must be detected to precisely locate the object system. …”
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  8. 8
    Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems

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

    Published 2011
    “…The main idea is the integration of optimal control and parameter estimation. In this work, a simplified model-based optimal control model with adjustable parameters is constructed. …”
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  9. 9
    On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing

    On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing by Kamal Z., Zamli, Alsariera, Yazan A., Nasser, Abdullah B., Alsewari, Abdulrahman A.

    Published 2015
    “…In doing so, this paper reviews two existing parameter free optimization algorithms involving Teaching Learning Based Optimization (TLBO) and Fruitfly Optimization Algorithm (FOA) in an effort to promote their adoption for CIT.…”
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  10. 10
    Finite impulse response optimizers for solving optimization problems

    Finite impulse response optimizers for solving optimization problems by Ab Rahman, Tasiransurini

    Published 2019
    “…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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  11. 11
    Finite impulse response optimizers for solving optimization problems

    Finite impulse response optimizers for solving optimization problems by Tasiransurini, Ab Rahman

    Published 2019
    “…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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  12. 12
    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
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  13. 13
    Enhanced gravitational search algorithm for nano-process parameter optimization problem / Norlina Mohd Sabri

    Enhanced gravitational search algorithm for nano-process parameter optimization problem / Norlina Mohd Sabri by Mohd Sabri, Norlina

    Published 2020
    “…Based on the capabilities of the metaheuristic algorithms, this research is proposing the enhanced Gravitational Search Algorithm (eGSA) to solve the nano-process parameter optimization problem. …”
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  14. 14
    An Optimal Design of Moving Objects Tracking Algorithm on FPGA

    An Optimal Design of Moving Objects Tracking Algorithm on FPGA by Elkhatib, Lina, Hussin, Fawnizu Azmadi, Xia, Likun, Sebastian , Patrick

    Published 2012
    “…This paper presents an optimal design and implementation of hardware system units for tracking moving objects on FPGA. …”
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  15. 15
    An optimal design of moving objects tracking algorithm on FPGA

    An optimal design of moving objects tracking algorithm on FPGA by Elkhatib, Lina Noaman, Hussin, Fawnizu Azmadi, Xia, Likun, Sebastian , Patrick

    Published 2010
    “…This paper presents an optimal design and implementation of hardware system units for tracking moving objects on FPGA. …”
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  16. 16
    OPTIMIZED ARCHITECTURE DESIGN AND IMPLEMENTATION OF OBJECT TRACKING ALGORITHM ON FPGA

    OPTIMIZED ARCHITECTURE DESIGN AND IMPLEMENTATION OF OBJECT TRACKING ALGORITHM ON FPGA by ABDELFATAH EL-KHATIB, LINA NOAMAN

    Published 2013
    “…The system need to be designed on a standard frame rate in such a way to achieve optimal performance in real time environment. …”
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  17. 17
    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). …”
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  18. 18
    Optimization of milling parameters using ant colony optimization

    Optimization of milling parameters using ant colony optimization by Mohd Saupi, Mohd Sauki

    Published 2008
    “…The simulation based on ACO algorithm are successful develop and the optimization of parameters values is to maximize the production rate is obtain from the simulation.…”
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  19. 19
    An optimal design of moving objects tracking algorithm on FPGA

    An optimal design of moving objects tracking algorithm on FPGA by Elkhatib, Lina, Hussin, Fawnizu Azmadi, Xia, Likun, Sebastian , Patrick

    Published 2012
    “…��������This paper presents an optimal design and implementation of hardware system units for tracking moving objects on FPGA. …”
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  20. 20
    Improvement of horizontal streak on disparity map thru parameter optimization for stereo vision algorithm

    Improvement of horizontal streak on disparity map thru parameter optimization for stereo vision algorithm by Gan, Melvin Yeou Wei, Hamzah, Rostam Affendi, Nik Anwar, Nik Syahrim, Herman, Adi Irwan, Jamil Alsayaydeh, Jamil Abedalrahim

    Published 2024
    “…Then, the research continues to optimize the proposed local based SVDM algorithm through parameters optimization in obtaining the final disparity map. …”
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