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  1. 1
    Solving the integrated inventory supply chain problems using meta-heuristic methods / Seyed Mohsen Mousavi

    Solving the integrated inventory supply chain problems using meta-heuristic methods / Seyed Mohsen Mousavi by Seyed Mohsen , Mousavi

    Published 2018
    “…A Modified Particle Swarm Optimization (MPSO) algorithm, a Genetic Algorithm (GA), a modified fruit fly optimization algorithm (MFOA) and a simulated annealing (SA) algorithm were used to find the optimal solution. …”
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  2. 2
    Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm

    Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm by Shahrizal, Saat, Mohd Ashraf, Ahmad, Mohd Riduwan, Ghazali

    Published 2025
    “…The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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  3. 3
    Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm

    Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm by Shahrizal, Saat, Mohd Ashraf, Ahmad, Mohd Riduwan, Ghazali

    Published 2025
    “…The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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  4. 4
    Assisted History Matching by Using Recursive Least Square and Discrete Cosine Transform

    Assisted History Matching by Using Recursive Least Square and Discrete Cosine Transform by Abu Talib, Muhammad Ashraf

    Published 2014
    “…Thus, this project is carried to do assisted history matching and to determine whether Recursive least square as optimization method and Discrete cosine transform as parameter reduction method can be combined or not. …”
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    Final Year Project
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  5. 5
    Use of AR Block Processing for Estimating the State Variables of Power System

    Use of AR Block Processing for Estimating the State Variables of Power System by Mohd Nor, Nursyarizal, Jegatheesan, Ramiah, Perumal, Nallagownden

    Published 2008
    “…Samples of the local utility network for 103-bus parameter are collected and simulated using Burg and Modified Covariance algorithm to estimate the state variables. …”
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  6. 6
    Performance of amidoxime-modified poly(acrylonitrile- Co-acrylic acid) for removal of boron in aqueous solution

    Performance of amidoxime-modified poly(acrylonitrile- Co-acrylic acid) for removal of boron in aqueous solution by Lau, Kia Li

    Published 2019
    “…Meanwhile, the Artificial Neural Network (ANN) was simulated from experimental data and applied to optimize, develop and create prediction models for boron adsorption by AO-modified poly(AN-co-AA). …”
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  7. 7
    Development of an islanding detection scheme based on combination of slantlet transform and ridgelet probabilistic neural network in distributed generation

    Development of an islanding detection scheme based on combination of slantlet transform and ridgelet probabilistic neural network in distributed generation by Ahmadipour, Masoud

    Published 2019
    “…Furthermore, to evaluate the efficiency of the proposed modified differential evolution for the training of ridgelet probabilistic neural network, four statistical search techniques, namely, particle swarm optimization, genetic algorithm, simulated angling, and classical differential evolution are used and their results are compared. …”
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  8. 8
    Modelling of optimized hybrid debris flow using airborne laser scanning data in Malaysia

    Modelling of optimized hybrid debris flow using airborne laser scanning data in Malaysia by Lay, Usman Salihu

    Published 2019
    “…The general objective of the study was the development of optimized hybrid debris flow models using airborne laser scanning data and Machine learning algorithms in Malaysia. …”
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  9. 9
    Power prediction using the wind turbine power curve and data-driven approaches / Ehsan Taslimi Renani

    Power prediction using the wind turbine power curve and data-driven approaches / Ehsan Taslimi Renani by Ehsan Taslimi , Renani

    Published 2018
    “…To obtain the unknown vector of parameters of the MHTan, three heuristic optimization algorithms are employed to minimize the sum of squared residuals. …”
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  10. 10
    Modified artificial neural network (ANN) models for Malaysian construction costs indices (MCCI) data / Saadi Ahmad Kamaruddin

    Modified artificial neural network (ANN) models for Malaysian construction costs indices (MCCI) data / Saadi Ahmad Kamaruddin by Ahmad Kamaruddin, Saadi

    Published 2018
    “…Theoretically, the most common algorithm to train the network is the backpropagation (BP) algorithm which is based on the minimization of the ordinary least squares (LS) estimator in terms of mean squared error (MSE). …”
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  11. 11
    A New Technique To Design Coating Structure For Energy Saving Glass Using The Genetic Algorithm

    A New Technique To Design Coating Structure For Energy Saving Glass Using The Genetic Algorithm by Azmin, Farah Ayuni

    Published 2017
    “…After modifying these shapes using the Genetic algorithm and Parallel Genetic algorithm, the outputs are simulated in the Computer Simulation Technology (CST) simulation software. …”
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  12. 12
    Modified least trimmed squares method for face recognition / Nur Azimah Abdul Rahim

    Modified least trimmed squares method for face recognition / Nur Azimah Abdul Rahim by Abdul Rahim, Nur Azimah

    Published 2018
    “…It can be concluded that the modified algorithm decreases the biases, the variances and the mean squared errors of the LTS estimators. …”
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  13. 13
    Simplified adaptive linear neuron harmonics extraction algorithm for dynamic performance of shunt active power filter

    Simplified adaptive linear neuron harmonics extraction algorithm for dynamic performance of shunt active power filter by Mohd Zainuri, Muhammad Ammirrul Atiqi, Mohd Radzi, Mohd Amran, Che Soh, Azura, Mariun, Norman, Abd Rahim, Nasrudin

    Published 2016
    “…The proposed harmonics extraction is an innovative work over the established algorithm, known as Modified Widrow-Hoff ADALINE algorithm. …”
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  14. 14
    Optimization of turning parameters using genetic algorithm method

    Optimization of turning parameters using genetic algorithm method by Shah Izwandi, Mohd Zawawi

    Published 2008
    “…This study about development of optimization for turning parameters based on the Genetic Algorithm (GA). …”
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    Undergraduates Project Papers
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  15. 15
    Parameters optimization of surface grinding process with particles swarm optimization, gravitational search, and sine cosine algorithms: a comparative analysis

    Parameters optimization of surface grinding process with particles swarm optimization, gravitational search, and sine cosine algorithms: a comparative analysis by Asrul, Adam

    Published 2018
    “…The efficiency of the three algorithms are evaluated and compared with previous results obtained by other optimization methods on similar studies. …”
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  16. 16
    Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization

    Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization by Nur Iffah, Mohamed Azmi

    Published 2014
    “…Particle swarm optimization algorithm (PSO) is one of the artificial intelligence methods. …”
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  17. 17
    Optimization of turning parameters using ant colony optimization

    Optimization of turning parameters using ant colony optimization by Mohamad Nazri, Semoin

    Published 2008
    “…The project objectives are to develop Ant Colony Optimization (ACO) algorithm for CNC turning process and to optimize turning parameters for minimized production cost per unit. …”
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  18. 18
    Parameter estimation in double exponential smoothing using genetic algorithm / Foo Fong Yeng, Lau Gee Choon and Zuhaimy Ismail

    Parameter estimation in double exponential smoothing using genetic algorithm / Foo Fong Yeng, Lau Gee Choon and Zuhaimy Ismail by Foo, Fong Yeng, Lau, Gee Choon, Ismail, Zuhaimy

    Published 2014
    “…Trial and error often serves as the best method to determine the parameter. Therefore, a good optimization technique is required for identify the best parameter in minimizing the forecast errors. …”
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    Research Reports
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  19. 19
    Fitness-guided particle swarm optimization with adaptive Newton-Raphson for photovoltaic model parameter estimation

    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
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  20. 20
    Application Of Genetic Algorithms For Robust Parameter Optimization

    Application Of Genetic Algorithms For Robust Parameter Optimization by Belavendram, N.

    Published 2010
    “…Genetic algorithms (GA) are fairly recent in this respect but afford a novel method of parameter optimization. …”
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