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  1. 1
    Kernel and multi-class classifiers for multi-floor wlan localisation

    Kernel and multi-class classifiers for multi-floor wlan localisation by Abd Rahman, Mohd Amiruddin

    Published 2016
    “…The multi-class classification strategy is used to ensure quick estimation of the multi-class NN algorithms. …”
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  2. 2
    Distributed Online Averaged One Dependence Estimator (DOAODE) Algorithm for Multi-class Classification of Network Anomaly Detection System

    Distributed Online Averaged One Dependence Estimator (DOAODE) Algorithm for Multi-class Classification of Network Anomaly Detection System by R.Badlishah, Ahmad, Nawir, M., Amir, A, Yaakob, N, Mat Safar, A, Mohd Warip, M.N, Zunaidi, I

    Published 2019
    “…Therefore, this paper aims to develop an effective and efficient network anomaly detection system by using distributed online averaged one dependence estimator (DOAODE) classification algorithm for multi-class network data to overcome these issues. …”
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  3. 3
    Distributed Online Averaged One Dependence Estimator (DOAODE) Algorithm for Multi-class Classification of Network Anomaly Detection System

    Distributed Online Averaged One Dependence Estimator (DOAODE) Algorithm for Multi-class Classification of Network Anomaly Detection System by Badlishah, Ahmad, Nawir, M., Amir, A, Yaakob, N, Mat Safar, A, Mohd Warip, M.N, Zunaidi, I

    Published 2019
    “…Therefore, this paper aims to develop an effective and efficient network anomaly detection system by using distributed online averaged one dependence estimator (DOAODE) classification algorithm for multi-class network data to overcome these issues. …”
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  4. 4
    Scene illumination classification based on histogram quartering of CIE-Y component

    Scene illumination classification based on histogram quartering of CIE-Y component by Hesamian, Mohammad Hesam

    Published 2014
    “…The main purpose of any illumination estimation algorithm from any type and class is to estimate an accurate number as illumination. …”
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  5. 5
    Scan Matching and KNN Classification for Mobile Robot Localisation Algorithm

    Scan Matching and KNN Classification for Mobile Robot Localisation Algorithm by Addie Irawan, Hashim, Marni Azira, Markom, Abdul Hamid, Adom, Mohd Muslim Tan, E. S.

    Published 2017
    “…The localisation algorithm is developed using scan matching method which is incorporated with K-nearest neighbours (KNN) classification. …”
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  6. 6
    Development of Phasor Measurement Unit Based Fault Detection and Faulty Line Classification in Electrical Power System

    Development of Phasor Measurement Unit Based Fault Detection and Faulty Line Classification in Electrical Power System by Muhammad Qasim, Khan

    Published 2019
    “…This study first focuses on modifying the PMU model for standard test systems in a MATLAB Simulink environment. This model implements Non-Recursive Phasor Estimation (NRPE) algorithm. …”
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  7. 7
    Fingerprint classification : a BI-resolution approach to singular point extraction

    Fingerprint classification : a BI-resolution approach to singular point extraction by Leong, Chung Ern

    Published 2004
    “…Fingerprint has been used as a biometric feature for security reasons for a long time. …”
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  8. 8
    A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption

    A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

    Published 2023
    “…The fitness function used is the correlation function in the SKF algorithm to optimize the cipher image produced using the Lorenz system. …”
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  9. 9
    Apply and optimize machine learning algorithms for estimating battery health

    Apply and optimize machine learning algorithms for estimating battery health by Chin, Wai Yee

    Published 2025
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  10. 10
    Spectral Estimation And Supervised Classification Technique For Real Time Electromyography Pattern Recognition

    Spectral Estimation And Supervised Classification Technique For Real Time Electromyography Pattern Recognition by Burhan, Nuradebah

    Published 2018
    “…Electromyography (EMG) signal is a biomedical signal which measures physical activity of human muscle.It has been acknowledged to be widely used in rehabilitation or recovery application system assisting physiotherapist to monitor a patient’s physical strength,function,motion and overall well-being by addressing the underlying physical issues.In application system associated with rehabilitation,a signal processing and classification techniques are implemented to classify EMG signal obtained.For real time application in the rehabilitation, the classification is crucial issue.The success of the signal classification depends on the selection of the features that represent a raw EMG signal in the signal processing.Therefore,a robust and resilient denoising method and spectral estimation technique have been acknowledged as necessary to distinguish and detect the EMG pattern.The present study was undertaken to determine the characteristic of EMG features using denoising method and spectral estimation technique for assessing the EMG pattern based on a supervised classification algorithm.In the study,the combination of time-frequency domain (TFD) and time domain (TD) were identified as the preferred denoising method and spectral estimation techniques.In the first part of study, the recorded EMG signal filtered the contaminated noise by using wavelet transform (WT) approach which implemented discrete wavelet transform (DWT) method of the wavelet-denoising signal. …”
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  11. 11
    Fault classification in transmission line using single layer feed-forward network trained by extreme learning machine / Muhamad Azfar Abd Ghafar

    Fault classification in transmission line using single layer feed-forward network trained by extreme learning machine / Muhamad Azfar Abd Ghafar by Abd Ghafar, Muhamad Azfar

    Published 2015
    “…The results of this work show that fault classification using SLFN trained by ELM has high accuracy on estimating fault in transmission line system.…”
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  12. 12
    Fault classification in transmission line using single layer feed-forward network trained by extreme learning machine / Muhamad Azfar Abd Ghafar

    Fault classification in transmission line using single layer feed-forward network trained by extreme learning machine / Muhamad Azfar Abd Ghafar by Abd Ghafar, Muhamad Azfar

    Published 2015
    “…The results of this work show that fault classification using SLFN trained by ELM has high accuracy on estimating fault in transmission line system.…”
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  13. 13
    New Algorithm of Location Model based on Robust Estimators and Smoothing Approach

    New Algorithm of Location Model based on Robust Estimators and Smoothing Approach by Hamid, Hashibah

    Published 2017
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  14. 14
    An accurate algorithm of PMU-based wide area measurements for fault detection using positive-sequence voltage and unwrapped dynamic angles

    An accurate algorithm of PMU-based wide area measurements for fault detection using positive-sequence voltage and unwrapped dynamic angles by Muhammad Qasim, Khan, Musse Mohamud, Ahmed, Ahmed Mohamed, Ahmed Haidar

    Published 2022
    “…The aim is to allow accurate action-based performance for analysts in monitoring the transmission lines so that rapid actions can be taken during abnormal circumstances before the blackout occurs. Among different algorithms, this study focuses on modelling the non- recursive phasor estimation method in a power Simulink environment for a standard test system equipped with a developed algorithm to detect the fault zone. …”
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  15. 15
    Analysing the performance of classification algorithms on diseases datasets

    Analysing the performance of classification algorithms on diseases datasets by Lydia E.L., Sharmil N., Shankar K., Maseleno A.

    Published 2023
    “…The proposed classification algorithms measure the diseases using the disease datasets which estimates the accurate prediction. …”
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  16. 16
    An Analysis of Large Data Classification using Ensemble Neural Network

    An Analysis of Large Data Classification using Ensemble Neural Network by Mumtazimah, Mohamad, Zahrahtul Amani, Zakaria, Wan Nor Shuhadah, Wan Nik, Arifah, Che Alhadi

    Published 2017
    “…The estimates derived using Apriori method shows that proposed ensemble ANN algorithm with a different approach is feasible where such problem with a high number of inputs and classes can be solved with time complexity of O(n^k ) for some k, which is a type of polynomial. …”
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  17. 17
    Optimization and discretization of dragonfly algorithm for solving continuous and discrete optimization problems

    Optimization and discretization of dragonfly algorithm for solving continuous and discrete optimization problems by Bibi Amirah Shafaa, Emambocus

    Published 2024
    “…The steepest-ascent hill climbing algorithm is used as a local search technique to improve the exploitation of the adapted discrete DA. …”
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  18. 18
    Class binarization with self-adaptive algorithm to improve human activity recognition

    Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…Therefore, feature selection using Relief-f with self-adaptive Differential Evolution (rsaDE) algorithm is proposed to select the most significant features. …”
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  19. 19
    Magnetic resonance imaging sense reconstruction system using FPGA / Muhammad Faisal Siddiqui

    Magnetic resonance imaging sense reconstruction system using FPGA / Muhammad Faisal Siddiqui by Muhammad Faisal , Siddiqui

    Published 2016
    “…Complex multiplier, complex matrix multiplier and pseudo-inverse modules are designed according to the algorithmic needs to increase the efficiency of the system. …”
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  20. 20
    Machine-learning-based adaptive distance protection relay to eliminate zone-3 protection under-reach problem on statcom-compensated transmission lines

    Machine-learning-based adaptive distance protection relay to eliminate zone-3 protection under-reach problem on statcom-compensated transmission lines by Aker, Elhadi Emhemed Alhaaj Ammar

    Published 2020
    “…The intelligent algorithm ML-ADR fault classifier model could discriminate 10 different far-end short circuit fault types from two network topology changes with and without midpoint integrated STATCOM on the Matlab/Simulink power grid system model. …”
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