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  1. 1
    Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems

    Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems by Kek, Sie Long

    Published 2011
    “…The main idea is the integration of optimal control and parameter estimation. In this work, a simplified model-based optimal control model with adjustable parameters is constructed. …”
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  2. 2
    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm

    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

    Published 2008
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  3. 3
    Parameter estimation of essential amino acids in Arabidopsis thaliana using hybrid of bees algorithm and harmony search

    Parameter estimation of essential amino acids in Arabidopsis thaliana using hybrid of bees algorithm and harmony search by Aw, Mei Yee, Mohd Saberi, Mohamad, Chong, Chuii Khim, Safaai, Deris, Muhammad Akmal, Remli, Mohd Arfian, Ismail, Corchado, Juan Manuel, Omatu, Sigeru

    Published 2019
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  4. 4
    Two level Differential Evolution algorithms for ARMA parameters estimatio

    Two level Differential Evolution algorithms for ARMA parameters estimatio by Salami, Momoh Jimoh Emiyoka, Tijani, Ismaila, Aibinu, Abiodun Musa

    Published 2013
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    Proceeding Paper
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  5. 5
    Dynamic robust bootstrap method based on LTS estimators

    Dynamic robust bootstrap method based on LTS estimators by Midi, Habshah, Uraibi, Hassan Sami, Al-Talib, Bashar Abdul Aziz Majeed

    Published 2009
    “…The applications of bootstrap methods in regression analysis have drawn much attention to the statistics practitioners because of some practical reasons. In order to make reliable inferences about the parameters of a model, require that the parameter estimates are normally distributed. …”
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  6. 6
    Hybrid fuzzy-sliding mode observer design for estimation and advanced control of an ethylene polymerization process / Jarinah Mohd Ali

    Hybrid fuzzy-sliding mode observer design for estimation and advanced control of an ethylene polymerization process / Jarinah Mohd Ali by Jarinah , Mohd Ali

    Published 2017
    “…Observers are computational algorithms designed to estimate unmeasured state variables due to the lack of appropriate estimating devices or to replace the high-priced sensors in a plant. …”
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  7. 7
    Developing an intelligent system to acquire meeting knowledge in problem-based learning environments

    Developing an intelligent system to acquire meeting knowledge in problem-based learning environments by Chiang, A., Baba, M.S.

    Published 2006
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  8. 8
    A Bayesian parameter learning procedure for nonlinear dynamical systems via the ensemble Kalman filter

    A Bayesian parameter learning procedure for nonlinear dynamical systems via the ensemble Kalman filter by Ur Rehman, M.J., Dass, S.C., Asirvadam, V.S.

    Published 2018
    “…Within the parameter learning steps, the MCMC algorithm requires to perform state estimation for which the target distribution is constructed by using the Ensemble Kalman filter (EnKF). …”
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  9. 9
    Parameter estimation of K-distributed sea clutter based on fuzzy inference and Gustafson-Kessel clustering

    Parameter estimation of K-distributed sea clutter based on fuzzy inference and Gustafson-Kessel clustering by Davari, Atefeh, Marhaban, Mohammad Hamiruce, Mohd Noor, Samsul Bahari, Karimadini, Mohammad, Karimoddini, Ali

    Published 2011
    “…The main contribution of the proposed method is the ability to estimate the parameters, given a small number of data which will usually be the case in practical applications. …”
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  10. 10
    An Educational Tool Aimed at Learning Metaheuristics

    An Educational Tool Aimed at Learning Metaheuristics by Kader, Md. Abdul, Jamaluddin, Jamal A., Kamal Z., Zamli

    Published 2020
    “…In this paper, we introduce an education tool for learning metaheuristic algorithms that allows displaying the convergence speed of the corresponding metaheuristic upon setting/changing the dependable parameters. …”
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  11. 11
    A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment

    A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment by Ruzita, Ahmad

    Published 2013
    “…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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  12. 12
    Artificial intelligence techniques applied as estimator in chemical process systems - A literature survey

    Artificial intelligence techniques applied as estimator in chemical process systems - A literature survey by Ali, J.M., Hussain, Mohd Azlan, Tade, M.O., Zhang, J.

    Published 2015
    “…Hence, in this paper, we provide a broad literature survey of several AI algorithms implemented as estimators in chemical systems together with their advantages, limitations, practical implications and comparisons between one another to guide researchers in selecting and designing the AI-based estimators. …”
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  13. 13
    The computation of confidence intervals for the state parameters of power systems

    The computation of confidence intervals for the state parameters of power systems by Khan, Z., Razali, R.B., Daud, H., Nor, N.M., Fotuhi-Firuzabad, M., Krebs, K.L.

    Published 2016
    “…The research indicates that confidence intervals can yield addition useful information about the estimated parameters. Methods: The feasible interval estimates for the system state parameters have been modelled in this study by considering the random uncertainty in the processing measurements. …”
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  14. 14
    The computation of confidence intervals for the state parameters of power systems

    The computation of confidence intervals for the state parameters of power systems by Khan, Z., Razali, R.B., Daud, H., Nor, N.M., Fotuhi-Firuzabad, M., Krebs, K.L.

    Published 2016
    “…The research indicates that confidence intervals can yield addition useful information about the estimated parameters. Methods: The feasible interval estimates for the system state parameters have been modelled in this study by considering the random uncertainty in the processing measurements. …”
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  15. 15
    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde

    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

    Published 2022
    “…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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  16. 16
    Combining Recursive Least Square and Principal Component Analysis for Assisted History Matching

    Combining Recursive Least Square and Principal Component Analysis for Assisted History Matching by Md. Anuar, Nurul Syaza

    Published 2014
    “…Even though RLS is a simple and effective method to estimate parameters, RLS have stability problem when number of parameters is high. …”
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    Final Year Project
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  17. 17
    Missing value estimation methods for data in linear functional relationship model

    Missing value estimation methods for data in linear functional relationship model by Adilah Abdul Ghapor, Yong Zulina Zubairi, A.H.M. Rahmatullah Imon

    Published 2017
    “…The performance of EM and EMB are measured using mean absolute error, root-mean-square error and estimated bias. The results of the simulation study suggested that both EM and EMB methods are applicable to the LFRM with EMB algorithm outperforms the standard EM algorithm. …”
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  18. 18
    Application of image processing and adaptive neuro-fuzzy system for estimation of the metallurgical parameters of a flotation process

    Application of image processing and adaptive neuro-fuzzy system for estimation of the metallurgical parameters of a flotation process by Jahedsaravani, A., Massinaei, Mohammad, Marhaban, Mohammad Hamiruce

    Published 2016
    “…The authors have already developed some reliable algorithms for measurement of the froth surface visual parameters such as bubble size distribution, froth color, velocity and stability. …”
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  19. 19
    Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm

    Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm by Yap K.S., Abidin I.Z., Ahmad A.R., Hussien Z.F., Pok H.L., Ismail F.I., Mohamad A.M.

    Published 2023
    “…SVM is a classification technique developed by Vapnik [1] but a practical difficulty of using SVM is the selection of parameters such as C and kernel parameter, � in Gaussian RBF kernel. …”
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  20. 20
    A hybrid simple exponential smoothing-barnacles mating optimization approach for parameter estimation: Enhancing COVID-19 forecasting in Malaysia

    A hybrid simple exponential smoothing-barnacles mating optimization approach for parameter estimation: Enhancing COVID-19 forecasting in Malaysia by Azlan, Abdul Aziz, Zuriani, Mustaffa, Suzilah, Ismail, Nor Azriani, Mohamad Nor, Nurin Qistina, Mohamad Fozi

    Published 2025
    “…However, SES is seen to underperform compared to other models due to parameter selection and initial value setting. Therefore, this study aims to propose a new hybrid model, the Single Exponential Smoothing (SES)-Barnacles Mating Optimization (BMO) algorithm, to estimate the optimal smoothing parameter alpha and initial value that can improve the percentage of forecast accuracy. …”
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