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  1. 1
    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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  2. 2
    Finite impulse response optimizers for solving optimization problems

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

    Published 2019
    “…The classification of estimation-based metaheuristic algorithms has been introduced for solving optimization problems. …”
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  3. 3
    Finite impulse response optimizers for solving optimization problems

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

    Published 2019
    “…The classification of estimation-based metaheuristic algorithms has been introduced for solving optimization problems. …”
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  4. 4
    An enhanced segment particle swarm optimization algorithm for kinetic parameters estimation of the main metabolic model of Escherichia coli

    An enhanced segment particle swarm optimization algorithm for kinetic parameters estimation of the main metabolic model of Escherichia coli by Mohammed Adam, Kunna, Tuty Asmawaty, Abdul Kadir, Muhammad Akmal, Remli, Noorlin, Mohd Ali, Kohbalan, Moorthy, Noryanti, Muhammad

    Published 2020
    “…Hence, based on the aforementioned problems, the optimization algorithm methods played an important role in addressing these problems. …”
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  5. 5
    Simulated Kalman Filter: A Novel Estimation-based Metaheuristic Optimization Algorithm

    Simulated Kalman Filter: A Novel Estimation-based Metaheuristic Optimization Algorithm by Zuwairie, Ibrahim, Nor Hidayati, Abd Aziz, Nor Azlina, Ab. Aziz, Saifudin, Razali, Mohd Saberi, Mohamad

    Published 2016
    “…To evaluate the performance of the Simulated Kalman Filter algorithm, it is applied to 30 benchmark functions of CEC 2014 for real-parameter single objective optimization problems. …”
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  6. 6
    Optimal parameter estimation of permanent magnet synchronous motor by using Mothflame optimization algorithm / Abdolmajid Dejamkhooy and Sajjad Asefi

    Optimal parameter estimation of permanent magnet synchronous motor by using Mothflame optimization algorithm / Abdolmajid Dejamkhooy and Sajjad Asefi by Dejamkhooy, Abdolmajid, Asefi, Sajjad

    Published 2018
    “…Simulation results and their comparison with Particle Swarm Optimization based method show high performance and good ability of the proposed method in PMSM parameter estimation.…”
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  7. 7
    An Improved Hybrid of Particle Swarm Optimization and the Gravitational Search Algorithm to Produce a Kinetic Parameter Estimation of Aspartate Biochemical Pathways

    An Improved Hybrid of Particle Swarm Optimization and the Gravitational Search Algorithm to Produce a Kinetic Parameter Estimation of Aspartate Biochemical Pathways by Ahmad Muhaimin, Ismail, Mohd Saberi, Mohamad, Hairudin, Abdul Majid, Khairul Hamimah, Abas, Safaai, Deris, Zaki, Nazar, Siti Zaiton, Mohd Hashim, Zuwairie, Ibrahim, Muhammad Akmal, Remli

    Published 2017
    “…Computational approaches are required to estimate these parameters. The estimation is converted into multimodal optimization problems that require a global optimization algorithm that can avoid local solutions. …”
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  8. 8
    Application of conjugate gradient approach for nonlinear optimal control problem with model-reality differences

    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
    “…Specifically, the modified model-based optimal control problem is resulted. Here, the conjugate gradient approach is used to solve the modified model-based optimal control problem, where the optimal solution of the model used is calculated repeatedly, in turn, to update the adjusted parameters on each iteration step. …”
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  9. 9
    Application of conjugate gradient approach for nonlinear optimal control problem with model-reality difference

    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
    “…Specifically, the modified model-based optimal control problem is resulted. Here, the conjugate gradient approach is used to solve the modified model-based optimal control problem, where the optimal solution of the model used is calculated repeatedly, in turn, to update the adjusted parameters on each iteration step. …”
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  10. 10
    The development of parameter estimation method for Chinese hamster ovary model using black widow optimization algorithm

    The development of parameter estimation method for Chinese hamster ovary model using black widow optimization algorithm by Nurul Aimi Munirah, ., Muhammad Akmal, Remli, Noorlin, Mohd Ali, Hui, Wen Nies, Mohd Saberi, Mohamad, Khairul Nizar Syazwan, Wan Salihin Wong

    Published 2020
    “…Metaheuristic parameter estimation is an algorithm framework that is processed using some technique to generate a pattern or graph. …”
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  11. 11
    Estimation of photovoltaic models using an enhanced Henry gas solubility optimization algorithm with first-order adaptive damping Berndt-Hall-Hall-Hausman method

    Estimation of photovoltaic models using an enhanced Henry gas solubility optimization algorithm with first-order adaptive damping Berndt-Hall-Hall-Hausman method by Ramachandran, Murugan, Sundaram, Arunachalam, Ridha, Hussein Mohammed, Mirjalili, Seyedali

    Published 2024
    “…The existing literature extensively explores the utilization of powerful Metaheuristic Algorithms (MAs) to address the complex constrained optimization problem in PV systems and achieve optimal solutions. …”
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  12. 12
    Pendulum-like algorithm as a local search technique

    Pendulum-like algorithm as a local search technique by Abed I.A., Koh S.P., Sahari K.S.M., Tiong S.K., Younis H.A.-K., Abed A.A.

    Published 2023
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  13. 13
    Optimal parameter estimation of MISO system based on fuzzy numbers / Razidah Ismail ... [et al.]

    Optimal parameter estimation of MISO system based on fuzzy numbers / Razidah Ismail ... [et al.] by Ismail, Razidah, Ahmad, Tahir, Ahmad, Shamsuddin, Ahmad, Rashdi Shah

    Published 2006
    “…Thus, this paper discusses the development of a Fuzzy State Space algorithm for optimal parameter estimation in multiple-input single-output (MISO) system based on fuzzy numbers. …”
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  14. 14
    Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach

    Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach by Nurnajmin Qasrina Ann, ., Pebrianti, Dwi, Mohamad Fadhil, Abas, Bayuaji, Luhur

    Published 2022
    “…DNN techniques is suitable in solving nonlinear and complex problem. The most popular method to solve parameter estimation problem is using optimization algorithm that easily trap to local minima and poor in exploitation to find the good solutions. …”
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  15. 15
    A Kalman Filter Approach for Solving Unimodal Optimization Problems

    A Kalman Filter Approach for Solving Unimodal Optimization Problems by Zuwairie, Ibrahim, Nor Hidayati, Abdul Aziz, Nor Azlina, Ab. Aziz, Saifudin, Razali, Mohd Ibrahim, Shapiai, Sophan Wahyudi, Nawawi, Mohd Saberi, Mohamad

    Published 2015
    “…To evaluate the performance of the SKF algorithm in solving unimodal optimization problems, it is applied unimodal benchmark functions of CEC 2014 for real-parameter single objective optimization problems. …”
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  16. 16
    Development of optimization Alghorithm for uncertain non-linear dynamical system

    Development of optimization Alghorithm for uncertain non-linear dynamical system by Abdul Aziz, Mohd. Ismail, Yaacob, Nazeeruddin, Mohd. Said, Norfarizan, Hamzah, Nor Hazadura

    Published 2004
    “…An algorithm that definitely can satisfy the objectives is the Dynamic Integrated Systems Optimization and Parameter Estimation (DISOPE) algorithm. …”
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  17. 17
    A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption

    A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

    Published 2023
    “…Lastly, a new hybrid technique suggests tackling the current image encryption application problem by using the estimated parameters of chaotic systems with an optimization algorithm, the SKF algorithm. …”
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  18. 18
    Liquid Flow Enhancement using Natural Polymeric Additives: Effect of Concentration

    Liquid Flow Enhancement using Natural Polymeric Additives: Effect of Concentration by Abdulbari, Hayder A., Fiona Ling, Wang Ming

    Published 2016
    “…To evaluate the performance of the Simulated Kalman Filter algorithm, it is applied to 30 benchmark functions of CEC 2014 for real-parameter single objective optimization problems. …”
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  19. 19
    Parameter estimation in computational systems biology models: a comparative study of initialization methods in global optimization

    Parameter estimation in computational systems biology models: a comparative study of initialization methods in global optimization by Muhammad Akmal, Remli, Nor Syahidatul Nadiah, Ismail, Noor Azida, Sahabudin, Nor Bakiah, Abd Warif

    Published 2022
    “…Global optimization method based on an enhanced scatter search (ESS) algorithm is a suitable choice to address this issue. …”
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  20. 20
    Identifying and estimating solar cell parameters using an enhanced slime mould algorithm

    Identifying and estimating solar cell parameters using an enhanced slime mould algorithm by Logeswaary, Devarajah, Mohd Ashraf, Ahmad, Jui, Julakha Jahan

    Published 2024
    “…The proposed ESMA was used to resolve the problem of estimating PV parameters based on the empirical current-voltage (I-V) data. …”
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