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  1. 1

    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
    “…This study introduces a new approach for parameter optimization in the four-diode photovoltaic (PV) model, employing a Dynamic Fitness-Guided Particle Swarm Optimization (DFGPSO) algorithm and Enhanced Newton-Raphson (ENR) method. …”
    Article
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    Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms by Alswaitti, Mohammed Y. T.

    Published 2018
    “…Moreover, the balance between the exploration and exploitation processes in the DPSO framework is considered using a combination of (i) a kernel density estimation technique associated with new bandwidth estimation method and (ii) estimated multi-dimensional gravitational learning coefficients. …”
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    Thesis
  5. 5

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

    Published 2020
    “…Finally, the proposed sizing method is compared with a numerical sizing method to show the accuracy and efficiency of the proposed method. …”
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    Thesis
  6. 6

    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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    Article
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    Feedforward neural network for solving particular fractional differential equations by Admon, Mohd Rashid

    Published 2024
    “…This research aims to develop a scheme based on a feedforward neural network (FNN) with a vectorized algorithm (FNNVA) for solving FDEs in the Caputo sense (FDEsC) using selected first-order optimization techniques: simple gradient descent (GD), momentum method (MM), and adaptive moment estimation method (Adam). …”
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    Thesis
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    Ant colony optimization and genetic algorithm models for suspended sediment discharge estimation for gorgan-river, Iran by Mohammad Reza Pour, Omolbani

    Published 2011
    “…New models based on artificial intelligence models, namely; Ant Colony Optimization (ACO) and Genetic Algorithm (GA) are now being used more frequently to solve optimization problems. …”
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    Thesis
  11. 11

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

    Published 2007
    “…This paper presents the optimal design of a 3-phase rectifier power transformer supplying a dc load by Genetic Algorithm (GA). …”
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    Conference or Workshop Item
  12. 12

    On iterative low-complexity algorithm for optimal antenna selection and joint transmit power allocation under impact pilot contamination in downlink 5g massive MIMO systems by Mohammed Ahmed, Adeeb Ali

    Published 2020
    “…The optimization of the antenna selection and optimal transmission power with impact of pilot reuse sequences were achieved, by applying Newton’s method and the Lagrange multiplier. …”
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    Thesis
  13. 13

    Enhancing battery state of charge estimation through hybrid integration of barnacles mating optimizer with deep learning by Zuriani, Mustaffa, Mohd Herwan, Sulaiman

    “…In response to the growing importance of SoC estimation, this study introduces a hybrid approach called the Barnacles Mating Optimizer with Deep Learning (BMO-DL) for SoC of Nissan Leaf batteries. …”
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    Article
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    Analysis of multiexponential transient signals using interpolation-based deconvolution and parametric modeling techniques by Salami, Momoh Jimoh Eyiomika, Ismail, Z.

    Published 2003
    “…Direct deconvolution approach often leads to poor resolution of ihe estimated decay rates since the fast Fourier transform (FFT) algorithm is used to analyze the resulting deconvolved data. …”
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    Proceeding Paper
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    Optimizing high-density aquaculture rotifer Detection using deep learning algorithm by Alixson Polumpung, Kit Guan Lim, Min Keng Tan, Sitti Raehanah Muhamad Shaleh, Renee Ka Yin Chin, Kenneth Teo Tze Kin

    Published 2022
    “…In this paper, we present the method and performance to detect rotifer Brachionus plicatilis in 1ml sample automatically using deep learning algorithm YOLOv3. …”
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    Proceedings
  17. 17

    Cutting temperature and surface roughness optimization in CNC end milling using multi objective genetic algorithm by Al Hazza, Muataz, Adesta, Erry Yulian Triblas, Superianto, M. Y., Riza, Muhammad

    Published 2012
    “…Due to complexity of this machining optimization problem, a multi objective genetic algorithm (MOGA) has been applied to resolve the problem, and the results have been analyzed…”
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    Proceeding Paper
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    Application of Evolutionary Algorithm for Assisted History Matching by Zahari, Muhammad Izzat

    Published 2014
    “…Today, tremendous efforts are made to develop Automatic History Matching algorithms. While the automatic method focus on optimization which is normally computer based. …”
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    Final Year Project
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    Gravitational Search Algorithm Based LSTM Deep Neural Network for Battery Capacity and Remaining Useful Life Prediction With Uncertainty by Reza M.S., Hannan M.A., Mansor M.B., Ker P.J., Tiong S.K., Hossain M.J.

    Published 2025
    “…Moreover, the LSTM model hyperparameters are optimized using the GSA optimization technique. To evaluate the robustness of the proposed method, 15 prediction samples are generated to calculate the uncertainty levels (95% CI) of the predicted RUL. …”
    Article
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    Parameter estimation of multicomponent transient signals using deconvolution and ARMA modelling techniques by Salami, Momoh Jimoh Emiyoka, Sidek, Shahrul Na'im

    Published 2003
    “…In this method of analysis the exponential signal is converted to a convolution model whose input is a train of weighted delta function that contains the signal parameters to be determined.The resolution of the estimated decay rates is poor if the conventional fast Fourier transform (FFT) algorithm is used to analyse the resulting deconvolved data. …”
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    Article