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  1. 1
    MULTIVARIABLE CLOSED-LOOP SYSTEM IDENTIFICATION USING ITERATIVE LEAKY LEAST MEAN SQUARES METHOD

    MULTIVARIABLE CLOSED-LOOP SYSTEM IDENTIFICATION USING ITERATIVE LEAKY LEAST MEAN SQUARES METHOD by MOHAMED OSMAN, MOHAMED ABDELRAHIM

    Published 2017
    “…In this research. novel algorithms have been developed to: (I) isolate the less interacting channe Is using a modified partial correlation algorithm. (2) achieve unbiased and consistent parameter estimates using an iterative LLMS algorithm and (3) develop parsimonious models for closed-loop MIMO systems. …”
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  2. 2
    Iterative closed-loop identification of MIMO systems using ARX-based Leaky Least Mean Square Algorithm

    Iterative closed-loop identification of MIMO systems using ARX-based Leaky Least Mean Square Algorithm by Rahim, M.A., Ramasamy, M., Tufa, L.D., Faisal, A.

    Published 2014
    “…Closed-loop identification of MIMO systems is considered. An iterative Leaky Least Mean Squares (LLMS) algorithm is proposed for the development of ARX structure. …”
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  3. 3
    Parameter identification of thermoelectric modules using enhanced slime mould algorithm (ESMA)

    Parameter identification of thermoelectric modules using enhanced slime mould algorithm (ESMA) by Ponnalagu, Dharswini, Mohd Ashraf, Ahmad, Jui, Julakha Jahan

    Published 2024
    “…Competency of the proposed algorithm in generating the optimal parameters for TEMs was appraised based on 21 benchmarked design parameters, following the objective of root mean square error (RMSE) minimization between the temperature of both actual and estimated models. …”
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  4. 4
    Modified multi-verse optimizer for nonlinear system identification of a double pendulum overhead crane

    Modified multi-verse optimizer for nonlinear system identification of a double pendulum overhead crane by Julakha, Jahan Jui, Mohd Ashraf, Ahmad, Muhammad Ikram, Mohd Rashid

    Published 2021
    “…The HMVOSCA algorithm is used to tune the linear and nonlinear parameters to reduce the gap between the estimated results and the actual results. …”
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  5. 5
    A Stochastic Total Least Squares Solution of Adaptive Filtering Problem

    A Stochastic Total Least Squares Solution of Adaptive Filtering Problem by Javed, Shazia, Ahmad, Noor Atinah

    Published 2014
    “…The TLMS algorithm is computationally simpler than the other TLS algorithms and demonstrates a better performance as compared with the least mean square (LMS) and normalized least mean square (NLMS) algorithms. …”
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  6. 6
    Identification of continuous-time model of hammerstein system using modified multi-verse optimizer

    Identification of continuous-time model of hammerstein system using modified multi-verse optimizer by Most. Julakha, Jahan Jui

    Published 2021
    “…The statistical analysis value (mean) was taken from the parameter deviation index to see how much our proposed algorithm has improved. …”
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  7. 7
    Identification of continuous-time hammerstein model using improved archimedes optimization algorithm

    Identification of continuous-time hammerstein model using improved archimedes optimization algorithm by Islam, Muhammad Shafiqul, Mohd Ashraf, Ahmad, Cho, Bo Wen

    Published 2024
    “…Improved mean fitness function values were also revealed in the TRS (11.63%) and EMPS (69.63%) assessments, surpassing the conventional algorithm. …”
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  8. 8
    Analysis of Toothbrush Rig Parameter Estimation Using Different Model Orders in Real Coded Genetic Algorithm (RCGA)

    Analysis of Toothbrush Rig Parameter Estimation Using Different Model Orders in Real Coded Genetic Algorithm (RCGA) by Ainul, H. M. Y., Salleh, S. M., Halib, N., Taib, H., Fathi, M. S.

    Published 2024
    “…The influence of conventional genetic algorithm parameter - generation gap has been investigated too. …”
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  9. 9
    Real-time system identification of an unmanned quadcopter system using fully tuned radial basis function neural networks

    Real-time system identification of an unmanned quadcopter system using fully tuned radial basis function neural networks by Pairan, Mohammad Fahmi, Shamsudin, Syariful Syafiq, Mohd Anwar, Mohd Shazlan

    Published 2021
    “…To prevent the neurons and network parameters selection dilemma during trial and error approach, RBF with EMRAN training algorithm is proposed. …”
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  10. 10
    A multi-objective genetic type-2 fuzzy extreme learning system for the identification of nonlinear dynamic systems

    A multi-objective genetic type-2 fuzzy extreme learning system for the identification of nonlinear dynamic systems by Hassan, S., Khanesar, M.A., Jaafar, J., Khosravi, A.

    Published 2017
    “…This paper propose a novel hybrid learning algorithm for the design of IT2FLS. The proposed algorithm benefits from the combination of extreme learning machine (ELM) and non-dominated sorting genetic algorithm (NSGAII) to tune the parameters of the consequent and antecedent parts of the IT2FLS, respectively. …”
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  11. 11
    A novel quantum calculus-based complex least mean square algorithm (q-CLMS)

    A novel quantum calculus-based complex least mean square algorithm (q-CLMS) by Sadiq, A., Naseem, I., Khan, S., Moinuddin, M., Togneri, R., Bennamoun, M.

    Published 2022
    “…The proposed algorithm is based on Wirtinger calculus and is called as q- Complex Least Mean Square (q-CLMS) algorithm. …”
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  12. 12
    A novel quantum calculus-based complex least mean square algorithm (q-CLMS)

    A novel quantum calculus-based complex least mean square algorithm (q-CLMS) by Sadiq, A., Naseem, I., Khan, S., Moinuddin, M., Togneri, R., Bennamoun, M.

    Published 2022
    “…The proposed algorithm is based on Wirtinger calculus and is called as q- Complex Least Mean Square (q-CLMS) algorithm. …”
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  13. 13
    A novel quantum calculus-based complex least mean square algorithm (q-CLMS)

    A novel quantum calculus-based complex least mean square algorithm (q-CLMS) by Sadiq, A., Naseem, I., Khan, S., Moinuddin, M., Togneri, R., Bennamoun, M.

    Published 2023
    “…The proposed algorithm is based on Wirtinger calculus and is called as q- Complex Least Mean Square (q-CLMS) algorithm. …”
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  14. 14
    Real-time system identification of an unmanned quadcopter system using fully tuned radial basis function neural networks

    Real-time system identification of an unmanned quadcopter system using fully tuned radial basis function neural networks by Pairan, Mohammad Fahmi, Shamsudin, Syariful Syafiq, Yaakub, Mohd Fauzi, Mohd Anwar, Mohd Shazlan

    Published 2021
    “…To prevent the neurons and network parameters selection dilemma during trial and error approach, RBF with EMRAN training algorithm is proposed. …”
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  15. 15
    Modeling of vehicle trajectory using K-means and fuzzy C-means clustering

    Modeling of vehicle trajectory using K-means and fuzzy C-means clustering by Choong, Mei Yeen, Lorita Angeline, Chin, Renee Ka Yin, Yeo, Kiam Beng, Teo, Kenneth Tze Kin

    Published 2019
    “…Hence, the clustering of vehicle trajectory dataset for similar patterns identification is implemented with k-means and fuzzy c-means (FCM) clustering algorithm. …”
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  16. 16
    Analysis of toothbrush rig parameter estimation using different model orders in Real-Coded Genetic Algorithm (RCGA)

    Analysis of toothbrush rig parameter estimation using different model orders in Real-Coded Genetic Algorithm (RCGA) by Ainul, H. M. Y., Salleh, S. M., Halib, N., Taib, H., Fathi, M. S.

    Published 2018
    “…The influence of conventional genetic algorithm parameter - generation gap has been investigated too. …”
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  17. 17
    Using a novel algorithm in ultrasound images to detect renal stones

    Using a novel algorithm in ultrasound images to detect renal stones by Sania Eskandari, Saeed Meshgini, Ali Farzamnia

    Published 2021
    “…In this paper, three essential segmentation algorithms, namely Fuzzy C-means, K-means, and Expectation–Maximization algorithms, are proposed for the identification of renal stone in kidney ultrasound images. …”
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  18. 18
    NARX modelling for steam distillation pilot plant using binary particle swarm optimisation technique / Najidah Hambali

    NARX modelling for steam distillation pilot plant using binary particle swarm optimisation technique / Najidah Hambali by Hambali, Najidah

    Published 2019
    “…This study proposes a system identification of SDPP using NARX model. The model structure selection of polynomial NARX had been focused on Binary Particle Swarm Optimisation (BPSO) algorithm. …”
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  19. 19
    Optimization of modified Bouc–Wen model for magnetorheological damper using modified cuckoo search algorithm

    Optimization of modified Bouc–Wen model for magnetorheological damper using modified cuckoo search algorithm by Rosmazi, Rosli, Zamri, Mohamed

    Published 2021
    “…An engineering optimization application was chosen to evaluate the performance of the algorithm in complex engineering applications. The optimization task involved hysteresis parameter identification of the root mean square error between the model and an actual magnetorheological damper. …”
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  20. 20
    A new hybrid genetic algorithm-sarima-artificial neural network in forecasting Malaysian export amount of palm oil

    A new hybrid genetic algorithm-sarima-artificial neural network in forecasting Malaysian export amount of palm oil by Chai, Kah Chun

    Published 2021
    “…The traditional Seasonal Autoregressive Integrated Moving Average (SARIMA) model assumes that all the parameters in the non-seasonal and seasonal parameters are significant which will lead to inaccuracy in the model identification stage and increase the cost of reidentification. …”
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