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  1. 1

    A Novel Polytope Algorithm based on Nelder-mead method for localization in wireless sensor network by Gumaida, Bassam, Abubakar, Adamu

    Published 2024
    “…Methods: It is suggested that the objective function that will be optimized using NMM is the mean squared error of the range of all neighboring anchor nodes installed in the studied WSNs. …”
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    A comparative study of evolutionary algorithms and adapting control parameters for estimating the parameters of a single-diode photovoltaic module's model by Muhsen D.H., Ghazali A.B., Khatib T., Abed I.A.

    Published 2023
    “…Algorithms; Diodes; Errors; Iterative methods; Least squares approximations; Mean square error; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Coefficient of determination; Differential Evolution; Electromagnetism-like algorithm; Hybrid evolutionary algorithm; Photovoltaic; Photovoltaic modules; Root mean square errors; Single-diode models; Evolutionary algorithms; algorithm; comparative study; electromagnetic method; estimation method; experimental design; numerical method; parameterization; performance assessment; photovoltaic system…”
    Article
  4. 4

    Complex-valued nonlinear adaptive filters for noncircular signals by Cyprian, Amadi Chukwuemena

    Published 2017
    “…The augmented CNGD has shown low Means Square Error (MSE) capabilities and have optimal performance than the conventional algorithm. …”
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    Thesis
  5. 5

    Short term traffic forecasting based on hybrid of firefly algorithm and least squares support vector machine by Yusof, Yuhanis, Ahmad, Farzana Kabir, Kamaruddin, Siti Sakira, Omar, Mohd Hasbullah, Mohamed, Athraa Jasim

    Published 2015
    “…Experimental result indicates that the proposed FA-LSSVM generates lower error rate and a higher accuracy compared to a non-optimized LSSVM.Such a scenario indicates that FA-LSSVM would be a competitor method in the area of time series forecasting.…”
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    Article
  6. 6

    Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm by Reza M.S., Hannan M.A., Mansor M., Ker P.J., Rahman S.A., Jang G., Mahlia T.M.I.

    Published 2025
    “…Moreover, the LSA optimization technique is introduced to optimally determine the LSTM deep neural model hyperparameters including the number of hidden neurons, learn rate, epoch, learn rate drop factor, learn rate drop period, and gradient decay factor. …”
    Article
  7. 7

    Extraction of photovoltaic module model's parameters using an improved hybrid differential evolution/electromagnetism-like algorithm by Muhsen D.H., Ghazali A.B., Khatib T., Abed I.A.

    Published 2023
    “…Algorithms; Evolutionary algorithms; Mean square error; Optimization; Parameter estimation; Photovoltaic cells; Coefficient of determination; DEAM; Five parameters; Hybrid differential evolution; Improved differential evolutions; IV characteristics; Photovoltaic modules; Root mean square errors; Iterative methods; algorithm; artificial intelligence; electromagnetic method; error analysis; experimental study; photovoltaic system…”
    Article
  8. 8

    Optimized image enhancement of colour processing for retinal fundus image by Nurul Atikah, Mohd Sharif

    Published 2025
    “…Secondly, the enhanced Tuned Brightness Controlled Single-Scale Retinex with Hybrid Particle Swarm Optimization - Contrast stretching (eTBCSSR-HPSOCS) algorithm is introduced to tackle the limitations of the standard Particle Swarm Optimization (PSO) algorithm in HPSOCS, which is prone to local optima and exhibits low convergence rates. …”
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    Thesis
  9. 9

    Optimized image enhancement of colour processing for retinal fundus image by Nurul Atikah, Mohd Sharif

    Published 2025
    “…Secondly, the enhanced Tuned Brightness Controlled Single-Scale Retinex with Hybrid Particle Swarm Optimization - Contrast stretching (eTBCSSR-HPSOCS) algorithm is introduced to tackle the limitations of the standard Particle Swarm Optimization (PSO) algorithm in HPSOCS, which is prone to local optima and exhibits low convergence rates. …”
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    Thesis
  10. 10

    Multi-Objectives Optimization Of Energy Consumption Of IKM Bintulu Buildings Towards Energy Saving by Othman, Muhamad Naim

    Published 2017
    “…The method applied the Genetic Algorithm (GA) to umavel the multi-objective optimization problem that involved the power consumption and the comfort of the 200 occupants. …”
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    Thesis
  11. 11

    Surface roughness optimization in end milling using the multi objective genetic algorithm approach by Al Hazza, Muataz Hazza Faizi, Adesta, Erry Yulian Triblas, Riza, Muhammad, Mohammad Yuhan, Suprianto

    Published 2012
    “…This paper presents the optimization of machining parameters in end milling processes by integrating the genetic algorithm (GA) with the statistical approach. …”
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    Article
  12. 12

    Investigation of firefly algorithm and chaos firefly algorithm for load prequency control / Zaid Najid by Zaid, Najid

    Published 2015
    “…Result shows that the CFA is the best optimization method due to its robustness and consistency. …”
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    Thesis
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    Satellite attitude determination utilizing measurement sensor data and kalman filtering by Samaan, Malak A., Abdelrahman, Mohammad

    Published 2006
    “…This assessment was done by using Monte Carlo methods to simulate these sensors. Using only star measurements an optimal satellite orientation estimate is found using the method of least squares, and the particular algorithm invoked is referred to ESOQ2 method. …”
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    Parameters extraction of double diode photovoltaic module's model based on hybrid evolutionary algorithm by Muhsen D.H., Ghazali A.B., Khatib T., Abed I.A.

    Published 2023
    “…Algorithms; Diodes; Errors; Extraction; Iterative methods; Mean square error; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Differential evolution algorithms; Diode modeling; Electromagnetism-like algorithm; Fast convergence speed; Hybrid evolutionary algorithm; IV characteristics; Photovoltaic model; Root mean square errors; Evolutionary algorithms…”
    Article
  16. 16

    Time series predictive analysis based on hybridization of meta-heuristic algorithms by Mustaffa, Zuriani, Sulaiman, Mohd Herwan, Rohidin, Dede, Ernawan, Ferda, Kasim, Shahreen

    Published 2018
    “…The identified meta-heuristic methods namely Moth-flame Optimization (MFO), Cuckoo Search algorithm (CSA), Artificial Bee Colony (ABC), Firefly Algorithm (FA) and Differential Evolution (DE) are individually hybridized with a well-known machine learning technique namely Least Squares Support Vector Machines (LS-SVM). …”
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    Article
  17. 17

    Noise Cancellation method in assistive listening system by Noor Aliff, Noor Affande

    Published 2020
    “…Those algorithms were Least Means Square, Normalize-Least Means Square, Recursive Least Square, Simple SetMembership Algorithm and Dynamic Set-Membership Affine Projection Algorithm. …”
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    Undergraduates Project Papers
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    CUCKOO SEARCH OPTIMIZATION NEURAL NETWORK MODELS FOR FORECASTING LONG-TERM PRECIPITATION by Kuok, King Kuok, Chiu, Po Chan, Md. Rezaur, Rahman, Khairul Anwar, Mohamad Said

    Published 2024
    “…Technological developments in metaheuristic algorithms have introduced a different method for downscaling. …”
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    Book Chapter
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    Predicting the classification of heart failure patients using optimized machine learning algorithms by Ahmed, Marzia, Mohd Herwan, Sulaiman, Hassan, Md Maruf, Bhuiyan, Touhid

    Published 2025
    “…The optimized hyperparameters for the GBM model were identified using the AIW-PSO algorithm, which effectively balanced exploration and exploitation by adaptively adjusting inertia weights. …”
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    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
    “…In this study, the performance of these three algorithms in obtaining the optimal blade design based on the �436�45D are investigated and compared. …”
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    Thesis