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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
    Feature identification in a real surface metrology analysis by means of Double Iteration Sobel (DIS) / Ainaa Farhanah Mohd Razali

    Feature identification in a real surface metrology analysis by means of Double Iteration Sobel (DIS) / Ainaa Farhanah Mohd Razali by Mohd Razali, Ainaa Farhanah

    Published 2022
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  4. 4
    RSA Encryption & Decryption using JAVA

    RSA Encryption & Decryption using JAVA by Ramli, Marliyana

    Published 2006
    “…The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
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  5. 5
    Extended multiple models selection algorithms based on iterative feasible generalized least squares (IFGLS) and expectation-maximization (EM) algorithm

    Extended multiple models selection algorithms based on iterative feasible generalized least squares (IFGLS) and expectation-maximization (EM) algorithm by Nur Azulia, Kamarudin

    Published 2019
    “…Therefore, in this study SUREAutometrics is improvised using two MLE methods, which are iterative feasible generalized least squares (IFGLS) and expectation-maximization (EM) algorithm, named as SURE(IFGLS)-Autometrics and SURE(EM)-Autometrics algorithms. …”
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  6. 6
    VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern

    VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern by Angeline Teoh, Szu Fern

    Published 2012
    “…They are Cross Entropy and also Genetic Algorithm. CE is a new algorithm that was recently developed using probability. …”
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  7. 7
    Segmentation of flair magnetic resonance brain images using K-Means Clustering algorithm / Nur Nabilah Abu Mangshor

    Segmentation of flair magnetic resonance brain images using K-Means Clustering algorithm / Nur Nabilah Abu Mangshor by Abu Mangshor, Nur Nabilah

    Published 2010
    “…This project is about segmentation of FLAIR brain Magnetic Resonance Image (MRI) using K-Means Clustering algorithm. A prototype system of brain segmentation is developed by implementing K-Means Clustering algorithm. …”
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  8. 8
    Development of Iterative Minimum-Maximum Filter for Reducing Impulse Noise from Highly Corrupted Images

    Development of Iterative Minimum-Maximum Filter for Reducing Impulse Noise from Highly Corrupted Images by Jabir, Amjad Najim

    Published 2006
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  9. 9
    Comparison of Search Algorithms in Javanese-Indonesian Dictionary Application

    Comparison of Search Algorithms in Javanese-Indonesian Dictionary Application by Yana Aditia, Gerhana, Nur, Lukman, Arief Fatchul, Huda, Cecep Nurul, Alam, Undang, Syaripudin, Devi, Novitasari

    Published 2020
    “…Performance Testing is used to test the performance of algorithm implementations in applications. …”
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  10. 10
    A Mobile Application For Stock Price Prediction

    A Mobile Application For Stock Price Prediction by Choy, Yi Tou

    Published 2021
    “…The evaluation methods were Root Mean Square Error and Mean Absolute Error. The results show ARIMA has the least error among all five prediction algorithms. …”
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  11. 11
    Kelantan daily water level prediction model using hybrid deep-learning algorithm for flood forecasting

    Kelantan daily water level prediction model using hybrid deep-learning algorithm for flood forecasting by Loh, Eng Chuen

    Published 2021
    “…Next, a newly developed hybrid deep learning (DL) algorithm is proposed to predict the daily water level in selected rivers that flow through Kelantan. …”
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  12. 12
    Quantum-Behaved Lightning Search Algorithm to Improve Indirect Field-Oriented Fuzzy-PI Control for im Drive

    Quantum-Behaved Lightning Search Algorithm to Improve Indirect Field-Oriented Fuzzy-PI Control for im Drive by Hannan M.A., Ali J.A., Mohamed A., Amirulddin U.A.U., Tan N.M.L., Uddin M.N.

    Published 2023
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  13. 13
    Detection and Measurement System for Button Mushrooms Using Convolutional Neural Network

    Detection and Measurement System for Button Mushrooms Using Convolutional Neural Network by Yong, Lio Wei, Ambar, Radzi, Abd Wahab, Mohd Helmy, Abd Jamil, Muhammad Mahadi, Choon, Chew Chang

    Published 2024
    “…The performance of the YOLOv4 models was evaluated across various iterations ranging from 1000 to 6000 iterations. The model with 2000 iterations demonstrated the most effective performance based on Recall, Precision, F1-score, Time and Mean Average Precision metrics. …”
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  14. 14
    LASSO-type estimations for threshold autoregressive and heteroscedastic time series models.

    LASSO-type estimations for threshold autoregressive and heteroscedastic time series models. by Muhammad Jaffri Mohd Nasir

    Published 2020
    “…This is an iterative two-stage procedure, where the weighted conditional mean model is estimated in the first stage and the heteroscedastic weights are estimated in the second stage. …”
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  15. 15
    Advancing Multiband OFDM Channel Sounding: An Iterative Time Domain Estimation for Spectrally Constrained Systems

    Advancing Multiband OFDM Channel Sounding: An Iterative Time Domain Estimation for Spectrally Constrained Systems by Iqbal, A., Drieberg, M., Jeoti, V., Aziz, A.B.A., Stojanovic, G.M., Simic, M., Hussain, N.

    Published 2023
    “…However, these nulls can significantly affect the performance of channel estimation algorithms. This work proposes a novel Iterative Multiband (MB) Spectrally Constrained Time-Domain (SCTD) technique to developed to reduce the residual error of correlation due to spectrally constrained waveforms. …”
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  16. 16
    Modelling and estimation of vehicle tracking using and improved particle filter

    Modelling and estimation of vehicle tracking using and improved particle filter by Khong, Wei Leong

    Published 2013
    “…Subsequently, the developed algorithm has also reduced 50.2 % of the resampling particles when the target vehicle reappears but still partially occluded from the occlusion as compared to the fundamental resampling approach.…”
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  17. 17
    A guided hybrid k-means and genetic algorithm models for children handwriting legibility performance assessment / Norzehan Sakamat

    A guided hybrid k-means and genetic algorithm models for children handwriting legibility performance assessment / Norzehan Sakamat by Sakamat, Norzehan

    Published 2021
    “…The combined method is called Hybrid K-MeansCGA. Modifications of K-Means structures were done by inserting genetic algorithm operators and tuning the population. …”
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  18. 18
    Quasi-Newton type method via weak secant equations for unconstrained optimization

    Quasi-Newton type method via weak secant equations for unconstrained optimization by Lim, Keat Hee

    Published 2021
    “…Armijo condition is implemented in the algorithms to generate monotone property in each iteration. …”
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  19. 19
    Peningkatan halaju suapan maksimum penginterpolasi CNC dedenyut rujukan menggunakan pengaturcaraan selari

    Peningkatan halaju suapan maksimum penginterpolasi CNC dedenyut rujukan menggunakan pengaturcaraan selari by Ahmad Fakhri, Ab. Nasir

    Published 2011
    “…Maximum allowable feed rate for reference-pulse Computer Numerical-Control (CNC) system is limited by the interpolator iteration speed. In other word, it means higher iteration speed corresponds to higher maximum allowable feed rate. …”
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  20. 20
    Logistic regression methods for classification of imbalanced data sets

    Logistic regression methods for classification of imbalanced data sets by Santi Puteri Rahayu, -

    Published 2012
    “…These results can be seen as further explanation on the success of Truncated Newton method in TR-KLR and TR Iteratively Re-weighted Least Square (TR-IRLS) algorithm respectively, because of the equivalence of iterative method used by these algorithms. …”
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