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  1. 1
    Using genetic algorithms as image watermarking performance optimizer / Zuhaili Zahid

    Using genetic algorithms as image watermarking performance optimizer / Zuhaili Zahid by Zahid, Zuhaili

    Published 2008
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  2. 2
    Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms

    Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms by Ridha, Hussein Mohammed

    Published 2020
    “…The IEM algorithm uses the attraction-repulsion mechanism to change the positions of solutions towards the optimality. …”
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  3. 3
    A buffer-based online clustering for evolving data stream

    A buffer-based online clustering for evolving data stream by Islam, Md. Kamrul, Ahmed, Md. Manjur, Kamal Z., Zamli

    Published 2019
    “…This algorithm recursively updates the micro-cluster radius to its local optimal. …”
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  4. 4
    Performance analysis of PSO MPPT for photovoltaic (PV) system during irradiance changes / Kharismi Burhanudin

    Performance analysis of PSO MPPT for photovoltaic (PV) system during irradiance changes / Kharismi Burhanudin by Burhanudin, Kharismi

    Published 2018
    “…Particle swarm optimization is soft computing methods which follow the bird swarm to track maximum power from PV panel. …”
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  5. 5
    Extraction and reconstruction of retinal vasculature

    Extraction and reconstruction of retinal vasculature by M.H.A., Fadzil, L.I., Izhar, P.A., Venkatachalam, T.V.N., Karunakar

    Published 2007
    “…The reconstruction technique reduces the required number of seeds to near optimal for the region growing process. It also overcomes poor performance of current seed-based methods, especially with low and inconsistent contrast images as normally seen in vasculature regions of fundus images. …”
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    Citation Index Journal
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  6. 6
    Predictive Maximum Power Point Tracking for Proton Exchange Membrane Fuel Cell System

    Predictive Maximum Power Point Tracking for Proton Exchange Membrane Fuel Cell System by Jye Yun, Fam, Shen Yuong, Wong, Hazrul, Mohamed Basri, Mohammad Omar, Abdullah, Kasumawati, Lias, Saad, Mekhilef

    Published 2021
    “…It is confirmed that the proposed MPPT technique exhibits fast tracking of the MPP locus, outstanding accuracy, and robustness with respect to environmental changes. Furthermore, its MPP tracking time is at least five times faster than that of the particle swarm optimizer with the proportional-integral-derivative controller method.…”
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  7. 7
    Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning

    Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning by Safa, Soodabeh

    Published 2016
    “…Moreover, instead of concatenating feature vectors together and send to classifier, sparse coding and dictionary learning methods are used and instead of considering all features as one view (visual feature), K-SVD algorithm that is one of the famous algorithms for sparse representation is optimized and developed to multi-view model.The experimental results prove that the proposed methods has improved accuracy by 53.77% compared to concatenating features and classic K-SVD dictionary learning model as well.…”
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  8. 8
    Adaptive Similarity Component Analysis in Nonparametric Dynamic Environment

    Adaptive Similarity Component Analysis in Nonparametric Dynamic Environment by Sojodishijani, Omid

    Published 2011
    “…Experimental results on real and synthesized datasets with real and artificial changes demonstrate the performance of the proposed method in terms of accuracy and dimension reduction in dynamic environments. …”
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  9. 9
    Development of a scaled conjugate gradient algorithm for significant RF neural signal processing

    Development of a scaled conjugate gradient algorithm for significant RF neural signal processing by Mohd Norden, Muhammad Farid Akmal, Mohd Isa, Roshakimah, Mohd Isa, Mohd Roshalizi, S. Abdul Kadir, Ros Shilawani, Md Azli, Muhammad Hariz, Muhammad Akram, Amir Syarif

    Published 2025
    “…Scale Conjugate Gradient (SCG) algorithm is an efficient training method for ANN that accelerates the learning process and improves output accuracy. …”
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  10. 10
    PREDICTIVE MAXIMUM POWER POINT TRACKING (MPPT) ALGORITHM FOR PERMANENT EXCHANGE MEMBRANE FUEL CELL (PEMFC)

    PREDICTIVE MAXIMUM POWER POINT TRACKING (MPPT) ALGORITHM FOR PERMANENT EXCHANGE MEMBRANE FUEL CELL (PEMFC) by MOHD RIZZWAN, MINGGU

    Published 2022
    “…A comparison of PEMFC performances based on the proposed technique with other existing MPPT algorithms will be done to validate the algorithm performance. …”
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    Final Year Project Report / IMRAD
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  11. 11
    Sleep arousal events detection using PNN-GBMO classifier based on EEG and ECG signals: A hybrid-learning model

    Sleep arousal events detection using PNN-GBMO classifier based on EEG and ECG signals: A hybrid-learning model by Afsoon Badiei, Saeed Meshgini, Ali Farzamnia

    Published 2020
    “…A subset of the features is then applied into the probabilistic neural network optimized by Gases Brownian Motion Optimization (GBMO) algorithm. …”
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  12. 12
    Using genetic algorithms to optimise land use suitability

    Using genetic algorithms to optimise land use suitability by Pormanafi, Saeid

    Published 2012
    “…Second task is to determine the fitness function for the genetic algorithms. The third objective is to optimize the land use map using economic benefits. …”
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  13. 13
    Fault-tolerant power extraction strategy for photovoltaic energy systems

    Fault-tolerant power extraction strategy for photovoltaic energy systems by Boutasseta, Nadir, Ramdani, Messaoud, Mekhilef, Saad

    Published 2018
    “…The objective of this study is to propose a fault-tolerant control (FTC) strategy to detect the presence of abnormal operating conditions and reconfigure the MPPT procedure to search for the new suboptimal operating point. The FDI method is based on monitoring the PV panel generated power for the presence of abrupt changes; the MPPT reconfiguration is based on a combination between Incremental Conductance (IncCond) Algorithm and an Improved Current-based Particle Swarm Optimization (ICPSO) tracking technique. …”
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  14. 14
    Enhanced efficiency and stability photovoltaic systems integrating improved MPPT photovoltaic systems / Mohd Hazni Abdul Halim Shah

    Enhanced efficiency and stability photovoltaic systems integrating improved MPPT photovoltaic systems / Mohd Hazni Abdul Halim Shah by Abdul Halim Shah, Mohd Hazni

    Published 2025
    “…The primary objective was to design and evaluate an MPPT system that combines a Cuk converter with the P&O algorithm to optimize energy extraction at varying irradiance levels. …”
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    Student Project
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  15. 15
    Adapting perturbation voltage for variable speed micro-hydro using particle swarm optimization (PSO)

    Adapting perturbation voltage for variable speed micro-hydro using particle swarm optimization (PSO) by Kit, Guan Lim, Mohd Izzat Fikri Md Zainal, Min, Keng Tan, Ahmad Razani Haron, Chang, Yii Chai, Teo, Kenneth Tze Kin

    Published 2022
    “…Meanwhile, high perturbation signal will cause the fluctuation that led to unstable power production. Thus, new method was introduced which is Particle Swarm Optimization (PSO) that is expected to improve the performance of conventional MPPT. …”
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    Proceedings
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  16. 16
    A new teaching learning artificial bee colony based maximum power point tracking approach for assessing various parameters of photovoltaic system under different atmospheric conditions

    A new teaching learning artificial bee colony based maximum power point tracking approach for assessing various parameters of photovoltaic system under different atmospheric condit... by Dokala Janandra, Krishna Kishore

    Published 2024
    “…Besides, the performance of the Renewable Energy (RE)-based system has to be enriched with regard to settling time, accuracy, speed, and efficiency. Hence, to optimize the cost of integrating RES‘s through newly developed maximum power point tracking (MPPT) based optimization method such as grasshopper optimization algorithm (GOA) has been introduced. …”
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  17. 17
    Operational structural damage identification using de-noised modal feature in machine learning / Chen Shilei

    Operational structural damage identification using de-noised modal feature in machine learning / Chen Shilei by Chen , Shilei

    Published 2021
    “…In conclusion, the supervised learning method using FRF change is convenient and effective in identifying the damage state of the plate, and can be optimized through mode shape assessment. …”
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  18. 18
    Predictive Maximum Power Point Tracking for Proton Exchange Membrane Fuel Cell System

    Predictive Maximum Power Point Tracking for Proton Exchange Membrane Fuel Cell System by Jye Yun, Fam

    Published 2025
    “…Therefore, the newly designed predictive MPPT methods exhibit fast-tracking of the MPP locus, outstanding accuracy, and robustness to environmental changes. …”
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  19. 19
    PSO modelling and PID controlled of automatic fish feeder system

    PSO modelling and PID controlled of automatic fish feeder system by W Mahmud, Wan Muhammad Azlan

    Published 2020
    “…The optimum PID parameter value obtained by the auto tune method is = − 3.4854, = − 50.2207 and = 0.05815. In conclusion, the PID controller successfully improved the performance of the fish feeding system with the highest percentage of speed change of 92.59%.…”
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  20. 20
    Task-state EEG signal classification for spatial cognitive evaluation based on multiscale high-density convolutional neural network

    Task-state EEG signal classification for spatial cognitive evaluation based on multiscale high-density convolutional neural network by Wen, Dong, Li, Rou, Tang, Hao, Liu, Yijun, Wan, Xianglong, Dong, Xianling, Saripan, M. Iqbal, Lan, Xifa, Song, Haiqing, Zhou, Yanhong

    Published 2022
    “…Secondly, to enhance feature propagation and reduce the number of parameters, the dense network was connected after the multi-scale convolutional network, and the learning rate change function of the stochastic gradient descent algorithm was optimized to objectively evaluate the training effect. …”
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