Search Results - (( data application based algorithm ) OR ( parameters detection method algorithm ))

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  1. 1

    Comparative study of clustering-based outliers detection methods in circular-circular regression model by Siti Zanariah, Satari, Nur Faraidah, Muhammad Di, Yong Zulina, Zubairi, Abdul Ghapor, Hussin

    Published 2021
    “…This paper is a comparative study of several algorithms for detecting multiple outliers in circular-circular regression model based on the clustering algorithms. …”
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    Article
  2. 2

    Comparative study of clustering-based outliers detection methods in circular-circular regression model by Siti Zanariah Satari, Nur Faraidah Muhammad Di, Yong Zulina Zubairi, Abdul Ghapor Hussin

    Published 2021
    “…This paper is a comparative study of several algorithms for detecting multiple outliers in circular-circular regression model based on the clustering algorithms. …”
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    Article
  3. 3

    Comparative study of clustering-based outliers detection methods in circularcircular regression model by Siti Zanariah, Satari, Nur Faraidah, Muhammad Di, Yong Zulina, Zubairi, Abdul Ghapor, Hussin

    Published 2021
    “…This paper is a comparative study of several algorithms for detecting multiple outliers in circular-circular regression model based on the clustering algorithms. …”
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    Article
  4. 4

    Fraud detection in telecommunication using pattern recognition method / Mohd Izhan Mohd Yusoff by Mohd Yusoff, Mohd Izhan

    Published 2014
    “…The new algorithm is tested on simulated and real data where the results show it is capable of detecting fraud activities. …”
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    Thesis
  5. 5
  6. 6

    Failure detection analysis of grid-connected photovoltaic systems in tropical climate region / Nurmalessa Muhammad @ Atan by Muhammad @ Atan, Nurmalessa

    Published 2020
    “…A modified threshold-based technique was used to build the FD algorithm based on data from PV system installed at GERC UiTM, Malaysia. …”
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    Thesis
  7. 7

    Vibration-based structural damage detection and system identification using wavelet multiresolution analysis / Seyed Alireza Ravanfar by Seyed Alireza, Ravanfar

    Published 2017
    “…This resulted in the high accuracy of the damage detection algorithm. The second proposed method seeks to identify damage in the structural parameters of linear and nonlinear systems. …”
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    Thesis
  8. 8
  9. 9

    Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari by Satari, Siti Zanariah

    Published 2015
    “…Lastly, we consider the problem of detecting multiple outliers in circular regression models based on the clustering algorithm. …”
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    Thesis
  10. 10

    Reduced rank technique for joint channel estimation and joint data detection in TD-SCDMA systems by Marzook, Ali Kamil, Ismail, Alyani, Mohd Ali, Borhanuddin, Sali, Aduwati, Khalaf, Mohannad H., Khatun, Sabira

    Published 2013
    “…We exploit the rank deficient of H to reduce the number of parameters that characterizes this matrix. The adopted reduced rank technique is based on singular value decomposition algorithm. …”
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    Article
  11. 11

    Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan by Meisam , Gordan

    Published 2020
    “…In the modeling phase, amongst all DM algorithms, the applicability of machine learning, artificial intelligence and statistical data mining techniques were examined using Support Vector Machine (SVM), Artificial Neural Network (ANN) and Classification and Regression Tree (CART) to detect the hidden patterns in vibration data. …”
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    Thesis
  12. 12

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

    Published 2009
    “…We modified the classical bootstrapping algorithm by developing a mechanism based on the robust LTS method to detect the correct number of outliers in the each bootstrap sample. …”
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    Thesis
  13. 13

    Road damage detection for autonomous driving vehicles using YOLOv8 and salp swarm algorithm by Nik Ahmad Farihin, Mohd Zulkifli, Zuriani, Mustaffa, Mohd Herwan, Sulaiman

    Published 2025
    “…Consequently, this paper proposes a method to improve the detection accuracy of You Only Look Once version 8 (YOLOv8) using Salp Swarm Algorithm (SSA) for hyperparameter optimization, focusing on eight key parameters. …”
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    Article
  14. 14

    Modified least trimmed squares method for face recognition / Nur Azimah Abdul Rahim by Abdul Rahim, Nur Azimah

    Published 2018
    “…The genetic algorithm configuration for n (number of observations) and p (parameter) was changed to assess the performance of modified method. …”
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    Thesis
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    Evaluation of the Transfer Learning Models in Wafer Defects Classification by Jessnor Arif, Mat Jizat, Anwar, P. P. Abdul Majeed, Ahmad Fakhri, Ab. Nasir, Zahari, Taha, Yuen, Edmund, Lim, Shi Xuen

    Published 2022
    “…All the algorithms were pretrained from ImageNet data-base before training with the wafer defect images. …”
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    Conference or Workshop Item
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    Heart disease prediction using artificial neural network with ADAM optimization and harmony search algorithm by Alyaa Ghazi Mohammed, Mohd Zakree Ahmad Nazri

    Published 2025
    “…This performance is validated through rigorous comparative assessments against various classification algorithms and state-of-the-art methods, revealing notable advantages in terms of predictive precision, computational efficiency, and adaptability to real-world clinical scenarios. …”
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    Article
  19. 19

    Federated deep learning for automated detection of diabetic retinopathy by Zainal Abidin, Nadzurah, Ismail, Amelia Ritahani

    Published 2022
    “…Deep learning is a machine learning algorithm with potential for detecting the significance of DR. …”
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    Proceeding Paper
  20. 20

    Embedded fuzzy classifier for detection and classification of preseizure state using real EEG data by Qidwai, U., Malik, A.S., Shakir, M.

    Published 2014
    “…Electroencephalography (EEG) plays an important role, especially EEG based health diagnosis of brain disorder. However, the common clinical methods are insufficient when it comes to design an automated module to detect and predict partial seizure for epileptic patients. …”
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    Conference or Workshop Item