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  1. 1
    Particle swarm optimization (PSO) for CNC route problem

    Particle swarm optimization (PSO) for CNC route problem by Nur Azia Azwani, Ismail

    Published 2002
    “…We often see many of the method of Genetic Algorithm (GA), Ant Colony Optimization (ACO), Simulated Annealing Algorithm (SAA) and PSO are used for any optimization problems. …”
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    Undergraduates Project Papers
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  2. 2
    Data Analysis using Particle Swarm Optimization Algorithm

    Data Analysis using Particle Swarm Optimization Algorithm by Tai, Zu Jie

    Published 2015
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    Final Year Project / Dissertation / Thesis
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  3. 3
    A hybrid particle swarm optimization approach and its application to solving portfolio selection problems

    A hybrid particle swarm optimization approach and its application to solving portfolio selection problems by Shamshul Bahar, Yaakob, Prof. Madya, Watada, Junzo

    Published 2011
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  4. 4
    Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman

    Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman by Che Osman, Siti Eshah

    Published 2019
    “…In this study, a pattern based using Particle Swarm Optimization (PSO) is proposed named as Hexagon PSO (HPSO). …”
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  5. 5
    Adaptive mechanism for enhanced performance of shark smell optimization / Nur Atharah Kamarzaman, Shahril Irwan Sulaiman and Intan Rahayu Ibrahim

    Adaptive mechanism for enhanced performance of shark smell optimization / Nur Atharah Kamarzaman, Shahril Irwan Sulaiman and Intan Rahayu Ibrahim by Kamarzaman, Nur Atharah, Sulaiman, Shahril Irwan, Ibrahim, Intan Rahayu

    Published 2021
    “…Numerical results indicate that the ASSO algorithm strategy outperforms the basic SSO algorithm, Genertic Algorithm (GA), Particle Swarm Intelligence (PSO), Firefly Algorithm (FA), Artificial Bee Colony (ABC) and Teaching Learning Based Optimization (TBLO) in term of reaching for global solution.…”
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  6. 6
    Hybrid-discrete multi-objective particle swarm optimization for multi-objective job-shop scheduling

    Hybrid-discrete multi-objective particle swarm optimization for multi-objective job-shop scheduling by Anuar, Nurul Izah

    Published 2022
    “…This research first proposes an improved continuous MOPSO to address the rapid clustering problem that exists in the basic PSO algorithm using three improvement strategies: re-initialization of particles, systematic switch of best solutions and mutation on global best selection. …”
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  7. 7
    Parametric modelling of a TRMS using dynamic spread factor particle swarm optimisation

    Parametric modelling of a TRMS using dynamic spread factor particle swarm optimisation by Toha, Siti Fauziah, Abd Latiff, I., Mohamad, M., Tokhi, M Osman

    Published 2009
    “…The proposed method formulates a modified inertia weight algorithm by using a dynamic spread factor (SF). …”
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    Proceeding Paper
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  8. 8
    A hybrid prediction model for pipeline corrosion using Artificial Neural Network with Particle Swarm Optimization

    A hybrid prediction model for pipeline corrosion using Artificial Neural Network with Particle Swarm Optimization by Ee, L.K., Aziz, I.A.

    Published 2018
    “…This project aims to develop a hybrid prediction Model which can target specific corrosion damage mechanisms. The basic ANN Model will be improved by integrating the Particle Swarm Optimization (PSO) algorithm to achieve a better and optimal performance. …”
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  9. 9
    A hybrid prediction model for pipeline corrosion using Artificial Neural Network with Particle Swarm Optimization

    A hybrid prediction model for pipeline corrosion using Artificial Neural Network with Particle Swarm Optimization by Ee, L.K., Aziz, I.A.

    Published 2018
    “…This project aims to develop a hybrid prediction Model which can target specific corrosion damage mechanisms. The basic ANN Model will be improved by integrating the Particle Swarm Optimization (PSO) algorithm to achieve a better and optimal performance. …”
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  10. 10
    Long-term optimal planning for renewable based distributed generators and battery energy storage systems toward enhancement of green energy penetration

    Long-term optimal planning for renewable based distributed generators and battery energy storage systems toward enhancement of green energy penetration by ALAhmad A.K., Verayiah R., Shareef H.

    Published 2025
    “…To solve the optimization planning model, a hybrid optimization algorithm is proposed, combining the non-dominating sorting genetic algorithm (NSGAII) and multi-objective particle swarm optimization (MOPSO). …”
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  11. 11
    Tree physiology optimization on SISO and MIMO PID control tuning

    Tree physiology optimization on SISO and MIMO PID control tuning by Halim, A.H., Ismail, I.

    Published 2018
    “…A simulation of SISO control system and an industrial application of MIMO control are applied to demonstrate the effectiveness of the proposed algorithm and compared with other optimization methods such as particle swarm optimization, Zieglerâ��Nichols, Tyreusâ��Luyben and Chienâ��Hronesâ��Reswick methods. …”
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  12. 12
    Tree physiology optimization on SISO and MIMO PID control tuning

    Tree physiology optimization on SISO and MIMO PID control tuning by Halim, A.H., Ismail, I.

    Published 2018
    “…A simulation of SISO control system and an industrial application of MIMO control are applied to demonstrate the effectiveness of the proposed algorithm and compared with other optimization methods such as particle swarm optimization, Zieglerâ��Nichols, Tyreusâ��Luyben and Chienâ��Hronesâ��Reswick methods. …”
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  13. 13
    Metaheuristic-Based Neural Network Training And Feature Selector For Intrusion Detection

    Metaheuristic-Based Neural Network Training And Feature Selector For Intrusion Detection by Ghanem, Waheed Ali Hussein Mohammed

    Published 2019
    “…Those problems lend themselves to the realm of optimization. Considering the wide success of swarm intelligence methods in optimization problems, the main objective of this thesis is to contribute to the improvement of intrusion detection technology through the application of swarm-based optimization techniques to the basic problems of selecting optimal packet features, and optimal training of neural networks on classifying those features into normal and attack instances. …”
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  14. 14
    Solving unit commitment problem by using particle swarm optimization technique / Muhammad Aqil Ab Rahman

    Solving unit commitment problem by using particle swarm optimization technique / Muhammad Aqil Ab Rahman by Ab Rahman, Muhammad Aqil

    Published 2014
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  15. 15
    Scheduling scientific workflow using multiobjective algorithm with fuzzy resource utilization in multi-cloud environment

    Scheduling scientific workflow using multiobjective algorithm with fuzzy resource utilization in multi-cloud environment by Farid, Mazen, Latip, Rohaya, Hussin, Masnida, Abdul Hamid, Nor Asilah Wati

    Published 2020
    “…In this respect, this paper proposes a new multi-objective scheduling algorithm with Fuzzy resource utilization (FR-MOS) for scheduling scientific workflow based on particle swarm optimization (PSO) method. …”
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  16. 16
    A Preliminary Report on the Utilization of PSO for Solving the Hamiltonian Systems

    A Preliminary Report on the Utilization of PSO for Solving the Hamiltonian Systems by Irianto, Irianto

    Published 2014
    “…This method utilizes an algorithm called Particle Swarm Optimization or PSO. …”
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  17. 17
    Intelligently tuned weights based robust H∞ controller design for pneumatic servo actuator system with parametric uncertainty

    Intelligently tuned weights based robust H∞ controller design for pneumatic servo actuator system with parametric uncertainty by Ali, Hazem Ibrahim, Mohd Noor, Samsul Bahari, Bashi, Sinan Mahmod, Marhaban, Mohammad Hamiruce

    Published 2011
    “…This paper presents a new method for tuning the weighing functions to design an H∞ controller. Based on a particle swarm optimization (PSO) algorithm the, weighting functions are tuned. …”
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  18. 18
    Image watermarking optimization algorithms in transform domains and feature regions

    Image watermarking optimization algorithms in transform domains and feature regions by Tao, Hai

    Published 2012
    “…The achieved tradeoffs from these techniques between imperceptibility and robustness are controversial.To solve this problem,this study proposes the application of artificial intelligent techniques into digital watermarking by using discrete wavelet transform (DWT) and singular value decomposition (SVD).To protect the copyright information of digital images,the original image is decomposed according to two-dimensional discrete wavelet transform.Subsequently the preprocessed watermark with an affined scrambling transform is embedded into the vertical subband (HLm) coefficients in wavelet domain without compromising the quality of the image.The scaling factors are trained with the assistance of Particle Swarm Optimization (PSO).A new algorithmic framework is used to forecast feasibility of hypothesized watermarked images.In addition,the novelty is to associate the Hybrid Particle Swarm Optimization (HPSO),instead of a single optimization,as a model with SVD.To embed and extract the watermark,the singular values of the blocked host image are modified according to the watermark and scaling factors. …”
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  19. 19
    INTELLIGENT OPTIMIZATION OF INTERLINE POWER FLOW CONTROLLER IN TRANSMISSION SYSTEM

    INTELLIGENT OPTIMIZATION OF INTERLINE POWER FLOW CONTROLLER IN TRANSMISSION SYSTEM by MOHAMED ABDELGADIR, KHALID HAROUN

    Published 2010
    “…The optimal parameters are derived to minimize the transmission line losses using three intelligent optimization techniques, namely Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Simulated Annealing (SA). …”
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  20. 20
    A calibration framework for swarming ASVs' system design

    A calibration framework for swarming ASVs' system design by Zainal Abidin, Zulkifli

    Published 2012
    “…Swimming pool provides as a controlled calibration framework for the proposed swarming algorithm. The performance of the system is determined by firstly, its capability to allow the various robots to communicate amongst themselves in order to reach the desired location and secondly, the use of optimization in its searching strategy. …”
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