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  1. 1
    Model structure selection for a discrete-time non-linear system using genetic algorithm

    Model structure selection for a discrete-time non-linear system using genetic algorithm by Ahmad, Robiah, Jamaluddin , Hishamuddin, Hussain, Mohd. Azlan

    Published 2004
    “…In this paper, a methodology for model structure selection based on a genetic algorithm was developed and applied to non-linear discrete-time dynamic systems. …”
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  2. 2
    Model structure selection for a discrete-time non-linear system using a genetic algorithm

    Model structure selection for a discrete-time non-linear system using a genetic algorithm by Ahmad, R., Jamaluddin, H., Hussain, M. A.

    Published 2004
    “…In this paper, a methodology for model structure selection based on a genetic algorithm was developed and applied to non-linear discrete-time dynamic systems. …”
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  3. 3
    Model structure selection for a discrete-time non-linear system using a genetic algorithm

    Model structure selection for a discrete-time non-linear system using a genetic algorithm by Ahmad, R., Jamaluddin, H., Hussain, M. A.

    Published 2004
    “…In this paper, a methodology for model structure selection based on a genetic algorithm was developed and applied to non-linear discrete-time dynamic systems. …”
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  4. 4
    Model structure selection for a discrete-time non-linear system using a genetic algorithm

    Model structure selection for a discrete-time non-linear system using a genetic algorithm by Ahmad, R., Jamaluddin, H., Hussain, Mohd Azlan

    Published 2004
    “…In this paper, a methodology for model structure selection based on a genetic algorithm was developed and applied to non-linear discrete-time dynamic systems. …”
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  5. 5
    Position estimation comparison of a 3-D linear lateration algorithm with a reference selection technique

    Position estimation comparison of a 3-D linear lateration algorithm with a reference selection technique by Yaro, A.S., Sha�Ameri, A.Z., Kamel, N.

    Published 2018
    “…The position estimation (PE) accuracy of the system depends on several factors such as the number of ground receiving station (GRS)s deployed, the reference station used and the type of lateration algorithm. In this paper, the 3-D PE accuracy of a four-GRS linear lateration algorithm combined with a GRS reference pair selection (GREPS) technique is determined and compared with two different five-GRS linear lateration algorithms. …”
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  6. 6
    Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares

    Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares by Uraibi, Hassan Sami

    Published 2009
    “…The Ordinary Least Squares (OLS) method is often used to estimate the parameters of a linear model. …”
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  7. 7
    Modeling of widely-linear quaternion valued systems using hypercomplex algorithms

    Modeling of widely-linear quaternion valued systems using hypercomplex algorithms by Mohammed, Haydar Imad, Hashim, Fazirulhisyam, Che Ujang, Che Ahmad Bukhari

    Published 2015
    “…The data-driven optimal modeling and identification of widely-linear quaternion-valued synthetic systems is achieved by using a quaternion-valued gradient based algorithms. …”
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  8. 8
    Linear-PSO with binary search algorithm for DNA Motif Discovery / Hazaruddin Harun

    Linear-PSO with binary search algorithm for DNA Motif Discovery / Hazaruddin Harun by Harun, Hazaruddin

    Published 2015
    “…The Linear-PSO algorithm was the first version of improvement……”
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  9. 9
    An observation of different clustering algorithms and clustering evaluation criteria for a feature selection based on linear discriminant analysis

    An observation of different clustering algorithms and clustering evaluation criteria for a feature selection based on linear discriminant analysis by Tie, K. H., A., Senawi, Chuan, Z. L.

    Published 2022
    “…When the Gaussian mixture distribution algorithm is adopted, none of the criteria can consistently select features with the least number. …”
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  10. 10
    Linear-pso with binary search algorithm for DNA motif discovery / Hazaruddin Harun

    Linear-pso with binary search algorithm for DNA motif discovery / Hazaruddin Harun by Harun, Hazaruddin

    Published 2015
    “…The Linear-PSO algorithm was the first version of improvement. …”
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  11. 11
    Clustering Spatial Data Using a Kernel-Based Algorithm

    Clustering Spatial Data Using a Kernel-Based Algorithm by Awan, A. Majid, Md. Sap, Mohd. Noor

    Published 2005
    “…This paper presents a method for unsupervised partitioning of data using kernel methods which offer strength to deal with complex data non-linearly separable in input space. …”
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  12. 12
    Particle swarm optimization for NARX structure selection: application on DC motor model / Mohd Ikhwan Abdullah

    Particle swarm optimization for NARX structure selection: application on DC motor model / Mohd Ikhwan Abdullah by Abdullah, Mohd Ikhwan

    Published 2010
    “…This thesis was presents the nonlinear identification of a DC motor using Binary Particle Swarm Optimization (BPSO) algorithm, as a model structure selection method, replacing the typical Orthogonal Least Squares (OLS) used in system identification. …”
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  13. 13
    Depth linear discrimination-oriented feature selection method based on adaptive sine cosine algorithm for software defect prediction

    Depth linear discrimination-oriented feature selection method based on adaptive sine cosine algorithm for software defect prediction by Nasser, Abdullah, H.M. Ghanem, Waheed Ali, H.Y. Saad, Abdul-Malik, Hamed Abdul-Qawy, Antar Shaddad, A. Ghaleb, Sanaa A, Mohammed Alduais, Nayef Abdulwahab, Din, Fakhrud, Ghetas, Mohamed

    Published 2024
    “…To address these challenges, this research introduces a novel Depth Linear Discrimination-Oriented Feature Selection Method based on Adaptive Sine Cosine Algorithm, named Depth Adaptive Sine Cosine Feature Selection (DASC-FS). …”
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  14. 14
    Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy

    Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

    Published 2019
    “…The proposed algorithm is compared with the state-of-the-art feature selection algorithms using three different datasets. …”
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  15. 15
    A modified algorithm for species specific motif discovery

    A modified algorithm for species specific motif discovery by Syed Abdullah, Sharifah Lailee, Harun, Hazaruddin, Taib, Mohd Nasir

    Published 2010
    “…For this study, PSO was modified for discovering motif.The modified Linear-PSO is chosen even though it is a slower because linear search is not a choice but a necessary criteria for identifying motif of pig (Sus Scrofa).Pig motif identification is a critical for halal authentication.The modified Linear-PSO algorithm used linear number for population initializing and next position updating.For each cycle, only a particle called ‘target motif’ was selected and compared with other DNA sequences for fitness calculation. …”
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  16. 16
    Dynamic determinant matrix-based block cipher algorithm

    Dynamic determinant matrix-based block cipher algorithm by Juremi, Julia

    Published 2018
    “…The performance analysis in terms of processing speed of the encryption and decryption process of the DDBC algorithm shows minimal differences in both AES and DDBC algorithm despite of the difference method of transformation used in both algorithms. …”
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  17. 17
    System identification of PFC rectifier controller using non-linear autoregressive moving average with exogenous inputs (NARMAX) model / Mohd Benyamin Sabtu

    System identification of PFC rectifier controller using non-linear autoregressive moving average with exogenous inputs (NARMAX) model / Mohd Benyamin Sabtu by Sabtu, Mohd Benyamin

    Published 2010
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  18. 18
    Depth Map Estimation based on Linear Regression using Image Focus

    Depth Map Estimation based on Linear Regression using Image Focus by Malik , Aamir Saeed, Song, Taek Lyul, Choi, Tae-Sun

    Published 2011
    “…Then linear regression model is used to find lines that approximate these datasets. …”
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  19. 19
    Linear and stratified sampling-based deep learning models for improving the river streamflow forecasting to mitigate flooding disaster

    Linear and stratified sampling-based deep learning models for improving the river streamflow forecasting to mitigate flooding disaster by Afan H.A., Yafouz A., Birima A.H., Ahmed A.N., Kisi O., Chaplot B., El-Shafie A.

    Published 2023
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  20. 20
    A new stepsize for gradient method via weak secant equation

    A new stepsize for gradient method via weak secant equation by Leong, Wah June

    Published 2007
    “…The algorithm then selects the stepsizes along the negative gradient using a new approximation of the Hessian based on the weak secant equation. …”
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