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  1. 1
    Optimization Of Fuzzy Logic Controllers With Genetic Algorithm For Two-Part-Type And Re-Entrant Production Systems

    Optimization Of Fuzzy Logic Controllers With Genetic Algorithm For Two-Part-Type And Re-Entrant Production Systems by Homayouni, Seyed Mahdi

    Published 2008
    “…GDF and GSF controllers are evaluated for two test cases namely “two-part-type production line” and “re-entrant production system”. …”
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  2. 2
    Sustainable renewable energy resources utilization in rural areas

    Sustainable renewable energy resources utilization in rural areas by Woldeyohannes, A.D., Woldemichael, D.E., Baheta, A.T.

    Published 2016
    “…Results obtained from the transportation model have been validated based on other RE studies in the area. For the similar case study considered, it is noted that the minimized total cost obtained using transportation algorithm depicts an improvement in cost over integrated renewable energy system (IRES) models. …”
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  3. 3
    Sustainable renewable energy resources utilization in rural areas

    Sustainable renewable energy resources utilization in rural areas by Woldeyohannes, A.D., Woldemichael, D.E., Baheta, A.T.

    Published 2016
    “…Results obtained from the transportation model have been validated based on other RE studies in the area. For the similar case study considered, it is noted that the minimized total cost obtained using transportation algorithm depicts an improvement in cost over integrated renewable energy system (IRES) models. …”
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  4. 4
    Online auto-tuned proportional-integral controller using particle swarm optimization for dual active bridge DC-DC converter

    Online auto-tuned proportional-integral controller using particle swarm optimization for dual active bridge DC-DC converter by Suliana, Ab Ghani

    Published 2021
    “…Since the linear controller such as the proportional-integral (PI) controller has some flaws of stability and performance in the nonlinear system, a direct control voltage through a phase-shift angle, <p using particle swarm optimization (PSO), namely PSO-d was introduced to evaluate the DAB performance without a classic linear controller. …”
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  5. 5
    Design of low order quantitative feedback theory and H-infinity-based controllers using particle swarm optimisation for a pneumatic actuator system

    Design of low order quantitative feedback theory and H-infinity-based controllers using particle swarm optimisation for a pneumatic actuator system by Ali, Hazem I.

    Published 2010
    “…These algorithms are designed to achieve the robustness over a wide range of system parameters change and disturbances. …”
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  6. 6
    Robustness Analysis Of An Optimized Controller Via Particle Swarm Algorithm

    Robustness Analysis Of An Optimized Controller Via Particle Swarm Algorithm by Chong, Chee Soon, Ghazali, Rozaimi, Jaafar, Hazriq Izzuan, Syed Hussein, Syarifah Yuslinda, Md Rozali, Sahazati

    Published 2017
    “…The finding shows that the SMC that utilized the PSO algorithm parameters are capable to produce smaller robustness index values, which demonstrated better robustness characteristic in confront with the variation of the system parameter.…”
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  7. 7
    Software regression test case prioritization for object-oriented programs using genetic algorithm with reduced-fitness severity

    Software regression test case prioritization for object-oriented programs using genetic algorithm with reduced-fitness severity by Musa, Samaila, Md Sultan, Abu Bakar, Abd Ghani, Abdul Azim, Baharom, Salmi

    Published 2015
    “…One of the most important activities in software maintenance is Regression testing. The re-execution of all test cases during the regression testing is costly. …”
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  8. 8
    The PID controller parameter tuning based on a modified differential evolutionary optimization algorithm for the intelligent active vibration control of a combined single link robotics flexible manipulator

    The PID controller parameter tuning based on a modified differential evolutionary optimization algorithm for the intelligent active vibration control of a combined single link robo... by Moloody, Abbas, As’arry, Azizan, Hong, Tang Sai, Raja Kamil, ., Zolfagharian, Ali

    Published 2025
    “…This research suggests an evolutionary algorithm that incorporates the variational techniques mentioned above, which will be combined by a certain ratio, and the specific computational procedure. …”
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  9. 9
    Effect of parameters variation on the performance of particle swarm optimization algorithm for tag coverage problem of radio frequency identification network

    Effect of parameters variation on the performance of particle swarm optimization algorithm for tag coverage problem of radio frequency identification network by Nawawi, Azli, Hasnan, Khalid, Ngali, Zamani, Sidek, Noor Azizah

    Published 2016
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  10. 10
    Performance of particle swarm optimization under different range of direct current motor's moment of inertia / Mohd Azri Abdul Aziz

    Performance of particle swarm optimization under different range of direct current motor's moment of inertia / Mohd Azri Abdul Aziz by Abdul Aziz, Mohd Azri

    Published 2018
    “…A prevalent application is a Direct Current (DC) motor control system with variations in parameters value have been used. …”
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  11. 11
    A regression test case selection and prioritization for object-oriented programs using dependency graph and genetic algorithm

    A regression test case selection and prioritization for object-oriented programs using dependency graph and genetic algorithm by Musa, Samaila, Md Sultan, Abu Bakar, Abd Ghani, Abdul Azim, Baharom, Salmi

    Published 2014
    “…Regression testing is very important activity in software testing. The re-execution of all test cases during regression testing will be costly. …”
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  12. 12
    Hybrid Control of A Quadrotor System Carrying Suspended Payload With Parameter Variations

    Hybrid Control of A Quadrotor System Carrying Suspended Payload With Parameter Variations by Amalin Aisya binti Mohd Awi

    Published 2025
    thesis::master thesis
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  13. 13
    Improved Differential Evolution-Based MPPT Algorithm Using SEPIC for PV Systems Under Partial Shading Conditions and Load Variation

    Improved Differential Evolution-Based MPPT Algorithm Using SEPIC for PV Systems Under Partial Shading Conditions and Load Variation by Tey, Kok Soon, Mekhilef, Saad, Seyedmahmoudian, Mehdi, Horan, Ben, Oo, Amanullah Than, Stojcevski, Alex

    Published 2018
    “…The main contribution of the proposed algorithm are the following: capability in tracking GMPP and faster respond against load variation; optimization algorithm can search for the GMPP within a larger operating region as it is implemented by using a single-ended primary-inductor converter; and easy tuning as less parameter has to be set in the algorithm. …”
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  14. 14
    Performance of particle swarm optimization under different range of direct current motor's moment of inertia / Mohd Azri Abdul Aziz

    Performance of particle swarm optimization under different range of direct current motor's moment of inertia / Mohd Azri Abdul Aziz by Abdul Aziz, Mohd Azri

    Published 2018
    “…A prevalent application is a Direct Current (DC) motor control system with variations in parameters value have been used. …”
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  15. 15
    Decentralized Adaptive Pi With Adaptive Interaction Algorithm Of Wastewater Treatment Plant

    Decentralized Adaptive Pi With Adaptive Interaction Algorithm Of Wastewater Treatment Plant by Rahmat, Mohd Fua'ad, Rahmat, Mohd Fuaad, Abdul Wahab, Norhaliza, Che Razali, Mashitah, Gaya, Muhammad Sani, Samsudin, Sharatul Izah

    Published 2014
    “…Wastewater treatment plant (WWTP) is highly known with the variation and uncertainty of the parameters, making them a challenge to be tuned and controlled.In this paper, an adaptive decentralized Pi controller is developed for nonlinear activated sludge WWTP. …”
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  16. 16
    Deep learning in public health: Comparative predictive models for COVID-19 case forecasting

    Deep learning in public health: Comparative predictive models for COVID-19 case forecasting by Muhammad Usman Tariq, Muhammad Usman Tariq, Ismail, Shuhaida

    Published 2024
    “…The findings indicate that the selected deep learning algorithms were proficient in forecasting COVID-19 cases, although their efficacy varied across different models. …”
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  17. 17
    A review: Use of evolutionary algorithm for optimisation of machining parameters

    A review: Use of evolutionary algorithm for optimisation of machining parameters by Zolpakar, N. A., Mohd Fuad, Yasak, Pathak, Sunil

    Published 2021
    “…By optimising machining parameters, a particular machining process can produce better machining outcomes within equivalent resources. …”
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  18. 18
    Comparison of several improved versions of particle swarm optimizer algorithm for parameter estimation of squirrel-cage induction motors / Mohammad Yazdani-Asrami, Mehran Taghipour Gorjikolaie and S. Asghar Gholamian

    Comparison of several improved versions of particle swarm optimizer algorithm for parameter estimation of squirrel-cage induction motors / Mohammad Yazdani-Asrami, Mehran Taghipour... by Gorjikolaie, Mehran Taghipour, Gholamian, S. Asghar

    Published 2014
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  19. 19
    An analysis of the parameter modifications in varieties of harmony search algorithm

    An analysis of the parameter modifications in varieties of harmony search algorithm by Mansor, N. F., Abal Abas, Zuraida, Abdul Rahman, Ahmad Fadzli Nizam, Shibghatullah, Abdul Samad, Safiah , Sidek

    Published 2014
    “…A Harmony Search (HS) algorithm is a population based-meta-heuristics approach that is superior in solving diversified and large scale optimization problems. …”
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  20. 20
    Optimal variational mode decomposition and integrated extreme learning machine for network traffic prediction

    Optimal variational mode decomposition and integrated extreme learning machine for network traffic prediction by Jinmei Shi, Yu-Beng Leau, Kun Li, Huandong Chen

    Published 2021
    “…A Scalable Artificial Bee Colony (SABC) algorithm which has fewer adjustable parameters and can thus guarantee the accuracy and stability of the prediction mechanism is also proposed. …”
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