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  1. 1
    Optimal power flow based on fuzzy linear programming and modified Jaya algorithms

    Optimal power flow based on fuzzy linear programming and modified Jaya algorithms by Alzihaymee, Warid Sayel Warid

    Published 2017
    “…The first proposed approach is a multi-objective fuzzy linear programming optimization (MFLP) algorithm to solve the MOOPF problem. …”
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  2. 2
    A new modified differential evolution algorithm scheme-based linear frequency modulation radar signal de-noising

    A new modified differential evolution algorithm scheme-based linear frequency modulation radar signal de-noising by Al-Dabbagh, Mohanad Dawood, Al-Dabbagh, Rawaa Dawoud, Raja Abdullah, Raja Syamsul Azmir, Hashim, Fazirulhisyam

    Published 2015
    “…The main intention of this study was to investigate the development of a new optimization technique based on the differential evolution (DE) algorithm, for the purpose of linear frequency modulation radar signal de-noising. …”
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  3. 3
    Modified multi-verse optimizer for nonlinear system identification of a double pendulum overhead crane

    Modified multi-verse optimizer for nonlinear system identification of a double pendulum overhead crane by Julakha, Jahan Jui, Mohd Ashraf, Ahmad, Muhammad Ikram, Mohd Rashid

    Published 2021
    “…In the HMVOSCA algorithm, the new position updating mechanism of the traditional MVO method is modified based on the sine function and cosine function which is taken from the Sine Cosine Algorithm (SCA). …”
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  4. 4
    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification

    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification by Jamaluddin, Hishamuddin, Abd. Samad, M. F., Ahmad, Robiah, Yaacob, M. S.

    Published 2007
    “…The genetic algorithm approach is widely recognized as an effective and flexible optimization method for system identification. …”
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  5. 5
    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification

    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification by Jamaluddin, H., Samad, M. F. A., Ahmad, R., Yaacob, M. S.

    Published 2007
    “…he genetic algorithm approach is widely recognized as an effective and flexible optimization method for system identification. …”
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  6. 6
    Model structure selection for a discrete-time non-linear system using a genetic algorithm

    Model structure selection for a discrete-time non-linear system using a genetic algorithm by Ahmad, R., Jamaluddin, H., Hussain, M. A.

    Published 2004
    “…Genetic algorithms (GAs) have received significant interest from researchers and have been applied to various optimization problems. …”
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  7. 7
    Model structure selection for a discrete-time non-linear system using a genetic algorithm

    Model structure selection for a discrete-time non-linear system using a genetic algorithm by Ahmad, R., Jamaluddin, H., Hussain, M. A.

    Published 2004
    “…Genetic algorithms (GAs) have received significant interest from researchers and have been applied to various optimization problems. …”
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  8. 8
    Model structure selection for a discrete-time non-linear system using genetic algorithm

    Model structure selection for a discrete-time non-linear system using genetic algorithm by Ahmad, Robiah, Jamaluddin , Hishamuddin, Hussain, Mohd. Azlan

    Published 2004
    “…Genetic algorithms (GAs) have received significant interest from researchers and have been applied to various optimization problems. …”
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  9. 9
    Identification of continuous-time model of hammerstein system using modified multi-verse optimizer

    Identification of continuous-time model of hammerstein system using modified multi-verse optimizer by Most. Julakha, Jahan Jui

    Published 2021
    “…his thesis implements a novel nature-inspired metaheuristic optimization algorithm, namely the modified Multi-Verse Optimizer (mMVO) algorithm, to identify the continuous-time model of Hammerstein system. …”
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  10. 10
    Hybrid evolutionary optimization algorithms: A case study in manufacturing industry

    Hybrid evolutionary optimization algorithms: A case study in manufacturing industry by Vasant, P.

    Published 2014
    “…Such complex problems of vagueness and uncertainty can be handled by the hybrid evolutionary intelligence algorithms. In this chapter, a new hybrid evolutionary optimization based methodology using a specific non-linear membership function, named as modified S-curve membership function, is proposed. …”
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  11. 11
    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification

    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification by Abd Samad, Md Fahmi

    Published 2007
    “…The genetic algorithm approach is widely recognized as an effective and flexible optimization method for system identification. …”
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  12. 12
    Memoryless modified symmetric rank-one method for large-scale unconstrained optimization

    Memoryless modified symmetric rank-one method for large-scale unconstrained optimization by Modarres, Farzin, Abu Hassan, Malik, Leong, Wah June

    Published 2009
    “…In this study, we present a scaled memoryless modified Symmetric Rank-One (SR1) algorithm and investigate the numerical performance of the proposed algorithm for solving large-scale unconstrained optimization problems. …”
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  13. 13
    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
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  14. 14
    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. …”
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  15. 15
    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. …”
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  16. 16
    Model structure selection for a discrete-time non-linear system using a genetic algorithm

    Model structure selection for a discrete-time non-linear system using a genetic algorithm by Ahmad, R., Jamaluddin, H., Hussain, Mohd Azlan

    Published 2004
    “…Genetic algorithms (GAs) have received significant interest from researchers and have been applied to various optimization problems. …”
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  17. 17
    SINR improvement using Firefly Algorithm (FA) for Linear Constrained Minimum Variance (LCMV) beamforming technique

    SINR improvement using Firefly Algorithm (FA) for Linear Constrained Minimum Variance (LCMV) beamforming technique by Doroody C., Tiong S.K., Darzi S.

    Published 2023
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  18. 18
    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm

    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

    Published 2008
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  19. 19
    Performance evaluation of smoothed functional algorithm based methods for sigmoid-PID control optimization in MIMO twin-rotor systems

    Performance evaluation of smoothed functional algorithm based methods for sigmoid-PID control optimization in MIMO twin-rotor systems by Mok, Ren Hao, Mohd Ashraf, Ahmad

    Published 2024
    “…The effectiveness of these SFA variations in optimizing SPID controllers for a MIMO twin-rotor system is compared, offering insights into the control and optimization of complex non-linear systems.…”
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  20. 20
    Development of high quality speech compression system for Quranic recitation based on modified CELP algorithm

    Development of high quality speech compression system for Quranic recitation based on modified CELP algorithm by Gunawan, Teddy Surya, Kartiwi, Mira

    Published 2013
    “…In this paper, we developed a high quality speech compression for Quranic recitation by modifying Code Excited Linear Prediction (CELP) algorithm. …”
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