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  1. 1
    Genetic algorithm based method for optimal location placement of flexible ac transmission system devices for voltage profile improvement

    Genetic algorithm based method for optimal location placement of flexible ac transmission system devices for voltage profile improvement by Karami, Mahdi

    Published 2011
    “…This thesis present a genetic algorithm based method for placement of FACTS devices for voltage profile improvement. …”
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  2. 2
    On the Application of heuristic Method and Saddle Node Bifurcation for Optimal Placement of FACTS Devices in Power System

    On the Application of heuristic Method and Saddle Node Bifurcation for Optimal Placement of FACTS Devices in Power System by Mariun, Norman, Ab Kadir, Mohd Zainal Abidin, Karami, Mehdi

    Published 2011
    “…This study focuses on an optimal placement of five major types of FACTS devices, namely, Static Var Compensator (SVC), Thyristor Controlled Series Compensator (TCSC), Static Synchronous Compensator (STATCOM), Static Synchronous Series Compensator (SSSC) and Unified Power Flow Controller (UPFC) in power system network using a well-known and applicable heuristic method known as genetic algorithm to seek the optimum location and setting of these controllers in the system. …”
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  3. 3
    Optimally sizing of Static Var Compensator using Bees Algorithm for cost minimization / Norain Sahari

    Optimally sizing of Static Var Compensator using Bees Algorithm for cost minimization / Norain Sahari by Sahari, Norain

    Published 2010
    “…This thesis presents the application of Bees Algorithm (BA) technique to find the optimal sizing of Static Var Compensator (SVC) to achieve the power system economic generation and dispatch. …”
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  4. 4
    Determining optimal location of static VAR compensator by means of genetic algorithm

    Determining optimal location of static VAR compensator by means of genetic algorithm by Karami, Mahdi, Mariun, Norman, Ab Kadir, Mohd Zainal Abidin

    Published 2011
    “…The purpose of this paper is to study a practical and accurate heuristic method known as genetic algorithm (GA) which is used to find the optimal location of Static Var Compensator (SVC) and its appropriate size and setting. …”
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  5. 5
    Optimal placement of static VAR compensator using genetic algorithms

    Optimal placement of static VAR compensator using genetic algorithms by Mustafa, Mohd. Wazir, Wong, Yan Chiew

    Published 2008
    “…The developed algorithms have successfully obtained the best solution for optimal placement of SVC in the IEEE 9 buses system and TNB northern area 275kV 14-bus system…”
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  6. 6
    Optimal sizing of static VAR compensator using bees algorithm for cost minimization

    Optimal sizing of static VAR compensator using bees algorithm for cost minimization by Sahari, Norain, Azman, Zulkifli, Ngadiron, Zuraidah, Sim, Sy Yi, Mohd Noh, Faridah Hanim, Mustafa, Farahiyah, Zambri, Nor Aira, Norjali, Rasida

    Published 2020
    “…This paper presents the application of Bees Algorithm (BA) technique to find the optimal sizing of Static Var Compensator (SVC) to achieve the power system economic generation and dispatch. …”
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  7. 7
    Optimal design of three-phase static var compensation system

    Optimal design of three-phase static var compensation system by George M., Bakar M.B.B.A., Basu K.P.

    Published 2023
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  8. 8
    Optimal operation and control of hybrid power systems with stochastic renewables and FACTS devices: An intelligent multi-objective optimization approach

    Optimal operation and control of hybrid power systems with stochastic renewables and FACTS devices: An intelligent multi-objective optimization approach by Premkumar M., Hashim T.J.T., Ravichandran S., Sin T.C., Chandran R., Alsoud A.R., Jangir P.

    Published 2025
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  9. 9
    Optimal Placement Of FACTS Devices In Power System Using Computational Intelligence Based Method

    Optimal Placement Of FACTS Devices In Power System Using Computational Intelligence Based Method by Mohammad Haikal Bin Aziz

    Published 2023
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  10. 10
    Multistage artificial immune system for static var compensator planning

    Multistage artificial immune system for static var compensator planning by Siti Chadijah Mohd Nasir

    Published 2024
    text::Final Year Project
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  11. 11
    Optimal location and sizing of SVC using Particle Swarm Optimization technique

    Optimal location and sizing of SVC using Particle Swarm Optimization technique by Jumaat, S.A., Musirin, I., Othman, M.M., Mokhlis, Hazlie

    Published 2011
    “…This paper describes optimal location and sizing of static var compensator (SVC) based on Particle Swarm Optimization for minimization of transmission losses considering cost function. …”
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  12. 12
    Transmission loss minimization using SVC based on particle swarm optimization

    Transmission loss minimization using SVC based on particle swarm optimization by Jumaat, S.A., Musirin, I., Othman, M.M., Mokhlis, Hazlie

    Published 2011
    “…This paper describes optimal sizing of static var compensator (SVC) based on Particle Swarm Optimization for minimization of transmission losses considering cost function. …”
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  13. 13
    A genetic approach for gateway placement in wireless mesh networks

    A genetic approach for gateway placement in wireless mesh networks by Awadallah, Hashim, Hassan Abdalla Hashim, Aisha

    Published 2015
    “…Keywords: Wireless Mesh Network, Gateway Placement, Genetic Algorithm, optimization…”
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  14. 14
    Optimal Reactive Power Dispatch for Voltage Stability Improvement Considering Line Contingencies using PSO

    Optimal Reactive Power Dispatch for Voltage Stability Improvement Considering Line Contingencies using PSO by Nor Rul Hasma, Abdullah, I., Musirin

    Published 2013
    “…The proposed algorithm gives an optimal setting of control devices such as switchable VAR compensator and able to minimize total transmission losses, improved voltage stability and increase voltage profile of the system. …”
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  15. 15
    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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    Undergraduates Project Papers
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  16. 16
    Parameters optimization of surface grinding process with particles swarm optimization, gravitational search, and sine cosine algorithms: a comparative analysis

    Parameters optimization of surface grinding process with particles swarm optimization, gravitational search, and sine cosine algorithms: a comparative analysis by Asrul, Adam

    Published 2018
    “…The efficiency of the three algorithms are evaluated and compared with previous results obtained by other optimization methods on similar studies. …”
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  17. 17
    Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization

    Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization by Nur Iffah, Mohamed Azmi

    Published 2014
    “…Particle swarm optimization algorithm (PSO) is one of the artificial intelligence methods. …”
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  18. 18
    Optimization of turning parameters using ant colony optimization

    Optimization of turning parameters using ant colony optimization by Mohamad Nazri, Semoin

    Published 2008
    “…The project objectives are to develop Ant Colony Optimization (ACO) algorithm for CNC turning process and to optimize turning parameters for minimized production cost per unit. …”
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  19. 19
    Parameter estimation in double exponential smoothing using genetic algorithm / Foo Fong Yeng, Lau Gee Choon and Zuhaimy Ismail

    Parameter estimation in double exponential smoothing using genetic algorithm / Foo Fong Yeng, Lau Gee Choon and Zuhaimy Ismail by Foo, Fong Yeng, Lau, Gee Choon, Ismail, Zuhaimy

    Published 2014
    “…Trial and error often serves as the best method to determine the parameter. Therefore, a good optimization technique is required for identify the best parameter in minimizing the forecast errors. …”
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    Research Reports
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  20. 20
    Fitness-guided particle swarm optimization with adaptive Newton-Raphson for photovoltaic model parameter estimation

    Fitness-guided particle swarm optimization with adaptive Newton-Raphson for photovoltaic model parameter estimation by Premkumar M., Ravichandran S., Hashim T.J.T., Sin T.C., Abbassi R.

    Published 2025
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