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  1. 1
    Optimal parameter estimation of permanent magnet synchronous motor by using Mothflame optimization algorithm / Abdolmajid Dejamkhooy and Sajjad Asefi

    Optimal parameter estimation of permanent magnet synchronous motor by using Mothflame optimization algorithm / Abdolmajid Dejamkhooy and Sajjad Asefi by Dejamkhooy, Abdolmajid, Asefi, Sajjad

    Published 2018
    “…In the next step, the parameter identification as an optimization problem is solved by Moth-flame optimization, which is a novel nature-inspired heuristic algorithm. …”
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  2. 2
    Improved dung beetle optimization algorithm and finite element analysis for spindle optimization

    Improved dung beetle optimization algorithm and finite element analysis for spindle optimization by Haohao, Ma, As’arry, Azizan, Xuping, Wu, Ismail, Mohd Idris Shah, Ramli, Hafiz Rashidi, Saad, Mohd Sazli, Delgoshaei, Aidin

    Published 2024
    “…The obtained optimal parameters guide the construction of a finite element model, considering additional factors like stiffness and maximum stress. …”
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  3. 3
    Parameter extraction of single, double, and three diodes photovoltaic model based on guaranteed convergence arithmetic optimization algorithm and modified third order Newton Raphson methods

    Parameter extraction of single, double, and three diodes photovoltaic model based on guaranteed convergence arithmetic optimization algorithm and modified third order Newton Raphson methods by Mohammed Ridha, Hussein, Hizam, Hashim, Mirjalili, Seyedali, Othman, Mohammad Lutfi, Ya'acob, Mohammad Effendy, Ahmadipour, Masoud

    Published 2022
    “…Numerous research have reviewed and presented approaches for figuring out the PV models parameter optimization problem in the literature. …”
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  4. 4
    Modeling Of Curves And Surfaces Using Ght-Bernstein Basis Functions And Using Optimization Methods To Construct Developable Surfaces

    Modeling Of Curves And Surfaces Using Ght-Bernstein Basis Functions And Using Optimization Methods To Construct Developable Surfaces by Bibi, Samia

    Published 2024
    “…A Bézier model with shape parameters is an influential research topic in geometric modeling and CAGD. …”
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  5. 5
    PSO and Linear LS for parameter estimation of NARMAX/NARMA/NARX models for non-linear data / Siti Muniroh Abdullah

    PSO and Linear LS for parameter estimation of NARMAX/NARMA/NARX models for non-linear data / Siti Muniroh Abdullah by Abdullah, Siti Muniroh

    Published 2017
    “…System Identification, a discipline for constructing models from dynamic systems, consist of three major steps: structure selection, parameter estimation and model validation. …”
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  6. 6
    Nonlinear auto-regressive model structure selection using binary particle swarm optimization algorithm / Ahmad Ihsan Mohd Yassin

    Nonlinear auto-regressive model structure selection using binary particle swarm optimization algorithm / Ahmad Ihsan Mohd Yassin by Mohd Yassin, Ahmad Ihsan

    Published 2014
    “…This thesis proposes the application of a stochastic optimization algorithm called Binary Particle Swarm Optimization algorithm for structure selection of polynomial NARX/NARMA/NARMAX models. …”
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  7. 7
    Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach

    Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach by Nurnajmin Qasrina Ann, ., Pebrianti, Dwi, Mohamad Fadhil, Abas, Bayuaji, Luhur

    Published 2022
    “…This study constructs the flow of DNN based method with the K-Means algorithm. …”
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  8. 8
    Sediment load forecasting from a biomimetic optimization perspective: Firefly and Artificial Bee Colony algorithms empowered neural network modeling in �oruh River

    Sediment load forecasting from a biomimetic optimization perspective: Firefly and Artificial Bee Colony algorithms empowered neural network modeling in �oruh River by Katipo?lu O.M., Kartal V., Pande C.B.

    Published 2025
    “…4.457, and KGE = 0.737) compared to other models. Furthermore, the utilization of FA and ABC optimization techniques facilitated the optimization of the ANN model parameters. …”
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  9. 9
    Gravitational Search Algorithm based Long Short-term Memory Deep Neural Network for Battery Capacity and Remaining Useful Life Prediction with Uncertainty

    Gravitational Search Algorithm based Long Short-term Memory Deep Neural Network for Battery Capacity and Remaining Useful Life Prediction with Uncertainty by Reza M.S., Hannan M.A., Mansor M., Ker P.J., Tiong S.K., Hossain M.J.

    Published 2024
    “…The RUL prediction uncertainty with a 95% confidence interval (CI) is also analyzed. The GSA algorithm optimizes the hyperparameters of the LSTM network to construct an optimal model. …”
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  10. 10
    Deep continual learning for predicting blast-induced overbreak in tunnel construction / He Biao

    Deep continual learning for predicting blast-induced overbreak in tunnel construction / He Biao by He , Biao

    Published 2024
    “…Third, the overbreak prediction model is further integrated with metaheuristic algorithms, aiming to identify the optimal blasting parameters that can minimize overbreak. …”
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  11. 11
    Application of system identification method coupled with evolutionary algorithms for the optimization of power consumption in a pem fuel cell propulsion system / Suhadiyana Hanapi

    Application of system identification method coupled with evolutionary algorithms for the optimization of power consumption in a pem fuel cell propulsion system / Suhadiyana Hanapi by Hanapi, Suhadiyana

    Published 2018
    “…This thesis makes a number of key contributions to the advancement of fuel cell vehicle design within two main research areas; powertrain system design based on quality energy, and optimization system based on biology based algorithms. …”
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  12. 12
    Development of a hybrid PSO-ANN model for estimating glucose and xylose yields for microwave-assisted pretreatment and the enzymatic hydrolysis of lignocellulosic biomass

    Development of a hybrid PSO-ANN model for estimating glucose and xylose yields for microwave-assisted pretreatment and the enzymatic hydrolysis of lignocellulosic biomass by Mohammad, Saleem Ethaib, Omar, Rozita, Mustapa Kamal, Siti Mazlina, Awang Biak, Dayang Radiah, S., Syafiie

    Published 2018
    “…The PSO algorithm suggested an optimum number of neurons in the hidden layer as 15 and a learning rate of 0.761 these consequently used to construct the ANN model. …”
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  13. 13
    Reproducing kernel Hilbert space method for cox proportional hazard model

    Reproducing kernel Hilbert space method for cox proportional hazard model by Abdul Manaf, Nur'azah

    Published 2016
    “…This algorithm is used to determine the vector i a that enables us to find the optimal parameters of ƒ(x)which is simplified as F(x)= ∑aᵢK(x,xᵢ) . …”
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  14. 14
    3D prediction of tunneling-induced ground movements based on a hybrid ANN and empirical methods

    3D prediction of tunneling-induced ground movements based on a hybrid ANN and empirical methods by Hajihassani, M., Kalatehjari, R., Marto, A., Mohamad, H., Khosrotash, M.

    Published 2019
    “…To overcome these problems, the use of optimization algorithms to train ANNs is of advantage. …”
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  15. 15
    3D prediction of tunneling-induced ground movements based on a hybrid ANN and empirical methods

    3D prediction of tunneling-induced ground movements based on a hybrid ANN and empirical methods by Hajihassani, M., Kalatehjari, R., Marto, A., Mohamad, H., Khosrotash, M.

    Published 2020
    “…To overcome these problems, the use of optimization algorithms to train ANNs is of advantage. …”
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  16. 16
    Nonlinear least squares parameter estimation problem using Levenberg-Marquardt method

    Nonlinear least squares parameter estimation problem using Levenberg-Marquardt method by Kaw, Wei Ching, Kek, Sie Long, Sim, Sy Yi

    Published 2017
    “…For illustration, the related models for an exponential distribution with two unknown parameters, and for the average monthly high temperature with four unknown parameters are constructed. …”
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  17. 17
    Harmony Search Approach In The Strut And Tie Model To Optimise The Stress Distribution In A Concrete Box Girder

    Harmony Search Approach In The Strut And Tie Model To Optimise The Stress Distribution In A Concrete Box Girder by Lim, Alice Pei San

    Published 2021
    “…Optimisation using metaheuristic algorithm could provide an alternative for more efficien t STM construction. …”
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  18. 18
    Accurate localization method combining optimized hybrid neural networks for geomagnetic localization with multi-feature dead reckoning

    Accurate localization method combining optimized hybrid neural networks for geomagnetic localization with multi-feature dead reckoning by Yan, Suqing, Luo, Baihui, Sun, Xiyan, Xiao, Jianming, Ji, Yuanfa, Kamarul Hawari, Ghazali

    Published 2025
    “…First, we construct a five-dimensional hybrid LSTM (5DHLSTM) neural network model, and the 5DHLSTM network structure parameters are optimized via particle swarm optimization (PSO) to achieve geomagnetic localization. …”
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  19. 19
    System identification and pid control of toothbrush simulator system

    System identification and pid control of toothbrush simulator system by Mohd Yusoff, Ainul Husna

    Published 2019
    “…A real-time experiment has been conducted on the real system via the Matlab Simulink environment to construct the model. The model parameters are optimized with model order 2, 3 and 4 where each model order has been analyzed for ten (10) times iteration by the genetic algorithm in obtaining the accurate transfer function. …”
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  20. 20
    A DC/DC buck-boost converter-inverter-dc motor control based on model-free PID controller tuning by adaptive safe experimentation dynamics algorithm

    A DC/DC buck-boost converter-inverter-dc motor control based on model-free PID controller tuning by adaptive safe experimentation dynamics algorithm by Mohd Riduwan, Ghazali, Mohd Ashraf, Ahmad, Mohd Helmi, Suid, Mohd Zaidi, Mohd Tumari

    Published 2022
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