Search Results - (( variable detection method algorithm ) OR ( a simulation model algorithm ))

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  1. 1

    Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data by Baba, Ishaq Abdullahi

    Published 2022
    “…The results obtained from the simulation study and real data sets indicate that the proposed method possesses high detection power with minimal misclassification error compared to the MRCD and MDP methods. …”
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    Thesis
  2. 2

    Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification by Abd Samad, Md Fahmi

    Published 2011
    “…Identification studies using NARX (Nonlinear AutoRegressive with eXogenous input) models employing simulated systems and real plant data are used to demonstrate that the algorithm is able to detect significant variables and terms faster and to select a simpler model structure than other well-known EC methods.…”
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    Article
  3. 3

    Fault diagnostic algorithm for precut fractionation column by Heng, H. Y., Ali, Mohamad Wijayanuddin, Kamsah, Mohd. Zaki

    Published 2004
    “…The fatty acid precut fractionation column chosen as a case study is modeled by the commercial simulator, HYSYS.Plant. …”
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    Conference or Workshop Item
  4. 4

    Development of fault detection, diagnosis and control system identification using multivariate statistical process control (MSPC) by Ibrahim, Kamarul 'Asri, Ahmad, Arshad, Ali, Mohamad Wijayanuddin, Mak, Weng Yee

    Published 2006
    “…Shewhart Control Chart (SCC) and Range Control Chart (RCC) are used with the developed correlation coefficients for FDD. The developed FDD algorithm was implemented on a simulated distillation column which is a single equipment process. …”
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    Monograph
  5. 5

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

    Published 2015
    “…Later, we assess the performance of confidence interval for error concentration parameter for the new functional relationship model via simulation study. Lastly, we consider the problem of detecting multiple outliers in circular regression models based on the clustering algorithm. …”
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    Thesis
  6. 6

    Development of a rule-based fault diagnostic advisory system for precut fractionation column by Heng, Han Yann

    Published 2005
    “…It was developed using Borland C++ Builder 6.0 and had a user friendly interface. Plant model was simulated by using commercial simulator, HYSYS.PlantTM and verified with real plant data. …”
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    Thesis
  7. 7

    Robust Estimation Methods And Outlier Detection In Mediation Models by Fitrianto, Anwar

    Published 2010
    “…Mediation models refer to the relationships among three variables: an independent variables (IV), a potential mediating variable (M), and a dependent variable (DV). …”
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    Thesis
  8. 8

    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
  9. 9

    An Automated Method For Model-Plant Mismatch Detection And Correction In Process Plants Employing Model Predictive Control (MPC) by Ahmed Bahakim, Sami Saeed

    Published 2012
    “…A model-predictive controller (MPC) uses the process model to predict future outputs of the system. …”
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    Final Year Project
  10. 10

    A simple model-free butterfly shape-based detection (BSD) method integrated with deep learning CNN for valve stiction detection and quantification by Kamaruddin, B., Zabiri, H., Mohd Amiruddin, A.A.A., Teh, W.K., Ramasamy, M., Jeremiah, S.S.

    Published 2020
    “…This simple model-free butterfly shape-based detection (BSD) method uses Stenman's one parameter stiction model, which results in a distinctive â��butterflyâ�� pattern in the presence of stiction. …”
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    Article
  11. 11

    Detection of leak size and its location in a water distribution system by using K-NN / Nasereddin Ibrahim Sherksi by Sherksi, Nasereddin Ibrahim

    Published 2020
    “…The successfully achieved four set objectives inclusive of (1) a new classification model to detect water leakage, (2) analysis of the effects of leakage size on the variables within a WDS, i.e. flow, pressure, pipe volume, velocity and water demand, (3) locating and specifying the leakage size in the WDS, and (4) evaluate the performance of the designed K-NN algorithm for accurate leak detection. …”
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    Thesis
  12. 12

    Fault detection and diagnosis using correlation coefficients by Mak, Weng Yee

    Published 2005
    “…A fractionation column from a palm oil fractionation plant is chosen as the case study and the model of the case study is simulated in Matlab. …”
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    Thesis
  13. 13

    Fault detection and diagnosis using rule-based support system on fatty acid fractionation column by Yann, H. H., Ali, Mohamad Wijayanuddin, Kamsah, Mohd Zaki

    Published 2003
    “…Plant model was simulated by using an existing commercial process simulator-HYSYS. …”
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    Article
  14. 14

    Numerical Analysis of structural batteries response with the presence of uncertainty by Syahiir Kamil, Ahmad Kamal Ariffin, Abdul Hadi Azman, Mohamad Syazwan Zafwan Mohamad Suffian

    Published 2023
    “…The Constant Strain Triangle element with linear elastic behavior is used as a structural model to simplify the model. Uncertainty of the material properties and loading are modeled as Fuzzy Random Variables. …”
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    Article
  15. 15

    Preliminary study on fault detection using artificial neural network for water-cooled reactors by Abdul Karim, Julia, Lanyau, Tony, Maskin, Masleha, Anuar, M. A. S., Che Soh, Azura, Abdul Rahman, Ribhan Zafira

    Published 2020
    “…Using actual data from the reactor to train the multilayer network model with backpropagation algorithm. Referring to the real data from the reactor, the simulation results demonstrate a good correlation between the proposed model using ANN and the real plants with a residual mean of below 1%. …”
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    Article
  16. 16

    Numerical Analysis of Structural Batteries Response with the Presence of Uncertainty by Syahiir, Kamil, Mohamad Syazwan Zafwan, Mohamad Suffian, Ahmad Kamal Ariffin, Mohd Ihsan, Abdul Hadi, Azman

    Published 2023
    “…The Constant Strain Triangle element with linear elastic behavior is used as a structural model to simplify the model. Uncertainty of the material properties and loading are modeled as Fuzzy Random Variables. …”
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    Article
  17. 17

    On line fault detection for transmission line using power system stabilizer signals by Ali Falifla, Hamza AbuBeker

    Published 2007
    “…Then by using PST(Power System Toolbox) to build state variable models in small signal analysis, and for modeling of machines and control system for performing transient stability simulation of a power system, These dynamic models are coded as MATLAB functions. …”
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    Thesis
  18. 18

    Parametric and Semiparametric Competing Risks Models for Statistical Process Control with Reliability Analysis by Mohamed Elfaki, Faiz Ahmed

    Published 2004
    “…In this thesis we develop a modified Fine and Gray methods to increase the sensitivity of the models and these methods are tested and compared. …”
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    Thesis
  19. 19

    Wavelet based fault tolerant control of induction motor / Khalaf Salloum Gaeid by Gaeid, Khalaf Salloum

    Published 2012
    “…The fault detection algorithm identifies the time and location of each fault. …”
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    Thesis
  20. 20

    Model predictive control based on Lyapunov function and near state vector selection of four-leg inverter / Abdul Mannan Dadu by Abdul Mannan, Dadu

    Published 2018
    “…The proposed control algorithm takes advantage of a predefined Lyapunov control law which minimizes the required calculation time by the Lyapunov model equations just once in each control loop to predict future variables. …”
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    Thesis