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  1. 1

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

    Published 2011
    “…System identification is a method of determining a mathematical relation between variables and terms of a process based on observed input-output data. …”
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    Article
  2. 2

    Smoothed functional algorithm with norm-limited update vector for identification of continuous-time fractional-order Hammerstein Models by Mok, Ren Hao, Mohd Ashraf, Ahmad

    Published 2024
    “…This article proposes an identification method of continuous-time fractional-order Hammerstein model using smoothed functional algorithm with a norm-limited update vector (NL-SFA). …”
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    Article
  3. 3

    Identification of continuous-time hammerstein model using improved archimedes optimization algorithm by Islam, Muhammad Shafiqul, Mohd Ashraf, Ahmad, Cho, Bo Wen

    Published 2024
    “…This proposed algorithm also discerned linear and nonlinear subsystem variables within a continuous-time Hammerstein model utilizing input and output data. …”
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    Article
  4. 4

    Voltage stability margin identification using evolution programming learning algorithm / Zamzuhairi Darus by Darus, Zamzuhairi

    Published 2003
    “…Voltage stability problems have been one of the major concerns for electric utilities as a result of a system heavy loading. This project proposed on an investigation on the voltage stability margin identification using evolution programming learning algorithm. …”
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    Thesis
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    Gas Identi cation by Using a Cluster-k-Nearest-Neighbor by Brahim Belhaouari, samir

    Published 2009
    “…Among the most serious limitations facing the success of future consumer gas identification systems are the drift problem and the real-time detection due to the slow response of most of todays gas sensors. …”
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    Article
  8. 8

    Modeling of cupping suction system based on system identification method by Kavindran, Suresh

    Published 2022
    “…Cupping suction plant identification utilizing a nonlinear model based on the modified Sine Cosine Algorithm (mSCA). …”
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    Undergraduates Project Papers
  9. 9

    Effects of user selected conditions on modeling of dynamic systems using adaptive fuzzy model by Yaacob, Mohd. Shafiek, Jamaluddin, Hishamuddin

    Published 2001
    “…In this paper, major properties of an adaptive fuzzy model as a system identifier when trained by the back-propagation algorithm are discussed. …”
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    Article
  10. 10

    Nonlinear identification for dengue fever / Herlina Abdul Rahim. by Abdul Rahim, Herlina

    Published 2009
    “…This thesis presents the development of a non-invasive system identification for the monitoring of the progression of dengue infection based on hemoglobin concentration. …”
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    Thesis
  11. 11

    Deterministic Mutation Algorithm As A Winner Over Forward Selection Procedure by Md Fahmi, Abd Samad

    Published 2016
    “…One of the steps in system identification is model structure selection which involves the selection of variables and terms of a model. …”
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    Article
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    A graphical user interface application for continuous-time identification of dynamical system by Rahmat, Mohd. Fua'ad, Omar, Rosli, Jamaluddin, Hishamuddin

    Published 2002
    “…This paper introduces a Graphical User Interface (GUI) application in system identification and parameter estimation of dynamic systems using Generalized Poisson Moment Functionals (GPMF) method based on Instrumental Variable (IV) algorithm. …”
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    Article
  14. 14

    Parameter Magnitude-Based Information Criterion For Optimum Model Structure Selection In System Identification by Mohd Nasir, Abdul Rahman

    Published 2020
    “…Model structure selection is among one of the steps in system identification and in order to carry out this, information criterion is developed. …”
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    Thesis
  15. 15

    Model input and structure selection in multivariable dynamic modeling of batch distillation column pilot plant / Ilham Rustam by Rustam, Ilham

    Published 2015
    “…It is established that a valid nonlinear multivariable case study is presented by the process plant via a systematic experiment conducted to justify the adopted nonlinear system identification. The implementation of Nonlinear Auto-Regressive with exogenous input (NARX) technique was then explored in this study to prove its reliability as a comprehensive system identification approach which has been cited across various recorded process identification platforms. …”
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    Thesis
  16. 16

    Modeling of flood water level prediction using NNARX / Fazlina Ahmat Ruslan by Ahmat Ruslan, Fazlina

    Published 2015
    “…It is established that a valid nonlinear multivariable case study is presented by the process plant via a systematic experiment conducted to justify the adopted nonlinear system identification. The implementation of Nonlinear Auto-Regressive with exogenous input (NARX) technique was then explored in this study to prove its reliability as a comprehensive system identification approach which has been cited across various recorded process identification platforms. …”
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    Thesis
  17. 17

    A single measurement of combined Direct and indirect MPPT algorithm for mismatch PV module application / Mohd Najib Mohd Hussain by Mohd Hussain, Mohd Najib

    Published 2016
    “…A novel of combination direct and indirect (CoDId) MPPT algorithm is implemented for solving mismatch losses from existing PV system by employing the implementation of system identification approach. …”
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    Thesis
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    Development of biosignals-based multimodal biometric system by Osamah Sadeq Alhamdani

    Published 2014
    “…The success of any biometric system is dependent on the pre-processing, features and classification algorithms exploits. …”
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    Thesis
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    Systematic design of chemical reactors with multiple stages via multi-objective optimization approach by Mohd Fuad, Mohd Nazri, Hussain, Mohd Azlan

    Published 2015
    “…Specifically, multi-objective optimization method will be used to generate Pareto optimal solutions that characterize the non-inferior solutions set for the problem. Following the identification of path-dependent design variables, several (possibly conflicting) design objectives will be selected and solutions of the corresponding problem will be generated from multi-objective optimization algorithm. …”
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    Conference or Workshop Item