Search Results - (( parameter simulation study algorithm ) OR ( parameter detection method algorithm ))

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  1. 1
    Parameter estimation and outlier detection in linear functional relationship model / Adilah Abdul Ghapor

    Parameter estimation and outlier detection in linear functional relationship model / Adilah Abdul Ghapor by Adilah, Abdul Ghapor

    Published 2017
    “…The simulation results indicate that the proposed method is suitable to detect a single outlier. …”
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  2. 2
    Outlier detection in circular regression model using minimum spanning tree method

    Outlier detection in circular regression model using minimum spanning tree method by Nur Faraidah, Muhammad Di, Siti Zanariah, Satari, Roslinazairimah, Zakaria

    Published 2019
    “…The existence of outliers in a circular regression model can lead to many errors, for example in inferences and parameter estimations. Therefore, this study aims to develop new algorithms that can detect outliers by using the minimum spanning tree method. …”
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  3. 3
    The multiple outliers detection for circular univariate data using different agglomerative clustering algorithms

    The multiple outliers detection for circular univariate data using different agglomerative clustering algorithms by Nur Syahirah, Zulkipli, Siti Zanariah, Satari, Wan Nur Syahidah, Wan Yusoff

    Published 2024
    “…In univariate circular data, the presence of outliers is acclaimed will affect the parameter estimates and inferences. This study proposes the procedure of detecting multiple outliers, particularly for univariate circular data based on agglomerative clustering algorithms. …”
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  4. 4
    Comparative study of clustering-based outliers detection methods in circular-circular regression model

    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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  5. 5
    Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari

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

    Published 2015
    “…This study focuses on the parameter estimation and outlier detection for some types of the circular model. …”
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  6. 6
    Comparative study of clustering-based outliers detection methods in circular-circular regression model

    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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  7. 7
    Comparative study of clustering-based outliers detection methods in circularcircular regression model

    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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  8. 8
    DEVELOPMENT OF OE-BASED BROWN-FORSYTHE TEST ALGORITHM FOR CONTROL VALVE STICTION DETECTION

    DEVELOPMENT OF OE-BASED BROWN-FORSYTHE TEST ALGORITHM FOR CONTROL VALVE STICTION DETECTION by JOLENE DIANDRA, JAMES

    Published 2018
    “…Therefore, the main objective of the project is to develop an OE-based Brown-Forsythe test algorithm to effectively detect the presence of control valve stiction.In this study, the proposed OE model is developed using System Identification in MATLAB, where it is used to simulate the process output (PV). …”
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    Final Year Project Report / IMRAD
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  9. 9
    Defect recognition method for magnetic leakage detection in oil and gas steel pipes based on improved neural networks / Wang Jie ... [et al.]

    Defect recognition method for magnetic leakage detection in oil and gas steel pipes based on improved neural networks / Wang Jie ... [et al.] by Wang, Jie, Mohd. Shah, Mohd. Kamal, Choong, Wai Heng, Al-Azad, Nahiyan

    Published 2024
    “…Traditional BP networks face challenges, including parameter determination and slow convergence, addressed through genetic algorithms' global search capabilities. …”
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  10. 10
    Defect recognition method for magnetic leakage detection in oil and gas steel pipes based on improved neural networks

    Defect recognition method for magnetic leakage detection in oil and gas steel pipes based on improved neural networks by Wang Jie, Mohd. Kamal Mohd. Shah, Choong Wai Heng, Nahiyan Al-Azad

    Published 2024
    “…Traditional BP networks face challenges, including parameter determination and slow convergence, addressed through genetic algorithms' global search capabilities. …”
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  11. 11
    Voltage Variation Analysis By Using Gabor Transform

    Voltage Variation Analysis By Using Gabor Transform by Abdullah, Abdul Rahim, Tee, Wei Hown, Yusoff, Mohd Rahimi

    Published 2019
    “…The voltage variation signals are successfully detected by using the K-Nearest Neighbors (kNN) algorithm with the implementation of signal parameters extracted as the input on the classifier. …”
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  12. 12
    Fair bandwidth distribution marking and scheduling algorithm in network traffic classification

    Fair bandwidth distribution marking and scheduling algorithm in network traffic classification by Al-Kharasani, Ameen Mohammed Abdulkarem

    Published 2019
    “…Finally, propose a new method of obtaining optimal parameters dropping functions for Random Early Detection (RED) algorithm. …”
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  13. 13
    Vision-Based Autonomous Vehicle Driving Control System

    Vision-Based Autonomous Vehicle Driving Control System by Isa, Khalid

    Published 2005
    “…The important contribution of this study is the development of vehicle lane detection and tracking algorithm based on colour cue segmentation, Canny edge detection and Hough transform. …”
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  14. 14
    Prototype of channel coding algorithm on digital signal processing board / Ahmad Shafiq Razelan

    Prototype of channel coding algorithm on digital signal processing board / Ahmad Shafiq Razelan by Razelan, Ahmad Shafiq

    Published 2011
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  15. 15
    Vision-based autonomous vehicle driving control system

    Vision-based autonomous vehicle driving control system by Isa, Khalid

    Published 2005
    “…The important contribution of this study is the development of vehicle lane detection and tracking algorithm based on colour cue segmentation, Canny edge detection and Hough transform. …”
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  16. 16
    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 performances of the newly proposed methods are investigated extensively by real data sets and simulations study. …”
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  17. 17
    Application of neural networks in early detection and diagnosis of parkinson's disease

    Application of neural networks in early detection and diagnosis of parkinson's disease by Olanrewaju, Rashidah Funke, Sahari, Nur Syarafina, Aibinu, Abiodun Musa, Hakiem, Nashrul

    Published 2014
    “…This MLFNN with BP algorithm is simulated using MATLAB software. The dataset information used in this study was taken from the Oxford Parkinson’s Disease Detection Dataset. …”
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    Proceeding Paper
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  18. 18
    Outlier detection in circular regression model using minimum spanning tree method

    Outlier detection in circular regression model using minimum spanning tree method by Nur Faraidah, Muhammad Di, Siti Zanariah, Satari, Roslinazairimah, Zakaria

    Published 2019
    “…The existence of outliers in circular-circular regression model can lead to many errors, for example in inferences and parameter estimations. Therefore, this study aims to develop new algorithms that can detect outliers by using minimum spanning tree method. …”
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  19. 19
    Modified least trimmed squares method for face recognition / Nur Azimah Abdul Rahim

    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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  20. 20
    Em Approach on Influence Measures in Competing Risks Via Proportional Hazard Regression Model

    Em Approach on Influence Measures in Competing Risks Via Proportional Hazard Regression Model by Elfaki, Faiz. A. M.

    Published 2000
    “…A generated data where the failure times were taken as exponentially distributed was used to further compare these two methods of estimation. From the simulation study for this particular case, we can conclude that the EM algorithm proved to be more superior in terms of mean value of parameter estimates, bias and root mean square error. …”
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