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  1. 1
    Energy efficient path reconstruction in wireless sensor network using iPath

    Energy efficient path reconstruction in wireless sensor network using iPath by Hasan, Sazlinah, Abd, Wamidh Jwdat, Ariffin, Ahmad Alauddin

    Published 2019
    “…To achieve energy efficiency, it compresses the packet information by using GZIP tools in JAVA. Energy efficient iPath (E-iPath) is evaluated with several variations of nodes in WSN deployments as well as large-scale simulations. …”
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  2. 2
    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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  3. 3
    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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  4. 4
    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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  5. 5
    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
    “…The implementation of Particle Swarm Optimization (PSO) algorithm in optimizing Proportional-Integral-Derivative (PID) controller's parameters is a popular technique to improve the performance of a control system. …”
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  6. 6
    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection

    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

    Published 2022
    “…The simulation is implemented with iFogSim and java programming language. …”
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  7. 7
    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
    “…Also, it does not easily fall into local optima. The evolutionary algorithm can be used to optimize the number of its hidden layer nodes. …”
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  8. 8
    Optimization of an extended H-infinity controller for unmanned helicopter control using multiobjective differential evolution (MODE)

    Optimization of an extended H-infinity controller for unmanned helicopter control using multiobjective differential evolution (MODE) by Tijani, Ismaila Bayo, Akmeliawati, Rini, Legowo, Ari, Budiyono, Agus

    Published 2015
    “…Formulate the H-infinity control scheme as an extended H-infinity loop shaping design procedure (H-LSDP) with incorporation of v-gap metric for robustness to parametric variation. Then apply the MODE-based algorithm to optimize the weighting function of the control problem formulation for optimal performance. …”
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  9. 9
    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
    “…The implementation of Particle Swarm Optimization (PSO) algorithm in optimizing Proportional-Integral-Derivative (PID) controller's parameters is a popular technique to improve the performance of a control system. …”
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  10. 10
    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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  11. 11
    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing

    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

    Published 2011
    “…Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources. A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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  12. 12
    Ant colony optimization algorithm for load balancing in grid computing

    Ant colony optimization algorithm for load balancing in grid computing by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

    Published 2012
    “…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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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
    Design Optimization of 3-Phase Rectifier Power Transformers by Genetic Algorithm and Simulated Annealing

    Design Optimization of 3-Phase Rectifier Power Transformers by Genetic Algorithm and Simulated Annealing by K.S., Rama Rao, Md Hasan, Khairul Nisak

    Published 2008
    “…A discussion on the limitations and variation of GA parameters while minimizing the single and multi-objective functions satisfying the performance constraints on the proposed optimal design concludes the paper.…”
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  15. 15
    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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  16. 16
    Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar

    Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar by Md. Rasel, Sarkar

    Published 2019
    “…There is no particular study which focuses on the optimization and prediction of blades parameters using natural inspired algorithms namely Ant Colony Optimization (ACO), Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO) and Adaptive Neuro-fuzzy Interface System (ANFIS) respectively for optimal power coefficient (�436�45D ). …”
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  17. 17
    The effect of key parameters on the design of an optimized CAES power plant

    The effect of key parameters on the design of an optimized CAES power plant by Khalaji Assadi , M, Shamshirgaran , S.R, Defaee Rad, S

    Published 2017
    “…This paper deals with a modeled compressed air energy storage power plant which has been optimized thermodynamically through an efficient genetic algorithm code. …”
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  18. 18
    Design Optimization of 3-phase rectifier power transformers by Genetic Algorithm and Simulated Annealing

    Design Optimization of 3-phase rectifier power transformers by Genetic Algorithm and Simulated Annealing by K.S., Rama Rao, K.N., Mohd Hassan

    Published 2008
    “…A discussion on the limitations and variation of GA parameters while minimizing the single and multi-objective functions satisfying the performance constraints on the proposed optimal design concludes the paper.…”
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  19. 19
    Design Optimization of 3-phase rectifier power transformers by Genetic Algorithm and Simulated Annealing

    Design Optimization of 3-phase rectifier power transformers by Genetic Algorithm and Simulated Annealing by K.S., Rama Rao, K.N., Mohd Hassan

    Published 2008
    “…A discussion on the limitations and variation of GA parameters while minimizing the single and multi-objective functions satisfying the performance constraints on the proposed optimal design concludes the paper.…”
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  20. 20
    Genetic algorithm for design optimization of 3-phase semi-conductor rectifier power transformers

    Genetic algorithm for design optimization of 3-phase semi-conductor rectifier power transformers by K.S.R, Rao

    Published 2007
    “…A discussion on the limitations and variation of GA parameters while minimizing the single and multi-objective functions satisfying the performance constraints on the proposed optimal design concludes the paper. …”
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