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  1. 1
    Tree-based contrast subspace mining method

    Tree-based contrast subspace mining method by Florence Sia Fui Sze

    Published 2020
    “…Hence, this thesis presents the optimization of parameters values for the tree-based method by genetic algorithm. This thesis also presents the optimization of contrast subspace search of the tree-based method by genetic algorithm. …”
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  2. 2
    Battery remaining useful life estimation based on particle swarm optimization-neural network

    Battery remaining useful life estimation based on particle swarm optimization-neural network by Zuriani, Mustaffa, Mohd Herwan, Sulaiman

    Published 2024
    “…In conducting an analysis, the performance of the PSO NN model is compared with hybrid NN with Cultural Algorithm (CA-NN) and Harmony Search Algorithm (HSA-NN), as well as the standalone Autoregressive Integrated Moving Average (ARIMA). …”
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  3. 3
    Simulated Kalman Filter algorithms for solving optimization problems

    Simulated Kalman Filter algorithms for solving optimization problems by Nor Hidayati, Abdul Aziz

    Published 2019
    “…These algorithms are inspired by the estimation capability of the well-known Kalman filter estimation method. …”
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  4. 4
    Web Algorithm search engine based network modelling of Malaria Transmission

    Web Algorithm search engine based network modelling of Malaria Transmission by Eze, Monday Okpoto

    Published 2013
    “…The Hypertext Induced Topical Search (HITS) web search algorithm was adapted to implement a search engine, which uses the bipartite contact network as the input. …”
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  5. 5
    Scale-invariant and adaptive-search template matching for monocular visual odometry in low-textured environment

    Scale-invariant and adaptive-search template matching for monocular visual odometry in low-textured environment by Aqel, Mohammad O. A.

    Published 2016
    “…This method is one of the most effective methods for template matching. …”
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  6. 6
    Estimation of Transformers Health Index Based on Condition Parameter Factor and Hidden Markov Model

    Estimation of Transformers Health Index Based on Condition Parameter Factor and Hidden Markov Model by Selva A.M., Yahaya M.S., Azis N., Ab Kadir M.Z.A., Jasni J., Yang Ghazali Y.Z.

    Published 2023
    Conference Paper
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  7. 7
    Estimation of unemployement in Malaysia using fourth-order taylor’s series method and fourthorder runge kutta method / Nur Batrisyia Suhaimi

    Estimation of unemployement in Malaysia using fourth-order taylor’s series method and fourthorder runge kutta method / Nur Batrisyia Suhaimi by Suhaimi, Nur Batrisyia

    Published 2021
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  8. 8
    Estimation of transformers health index based on condition parameter factor and hidden Markov model

    Estimation of transformers health index based on condition parameter factor and hidden Markov model by Mohd Selva, Amran, Yahaya, Muhammad Sharil, Azis, Norhafiz, Ab Kadir, Mohd Zainal Abidin, Jasni, Jasronita, Yang Ghazali, Young Zaidey

    Published 2018
    “…Next, the emission probabilities for each of the condition parameter factors were derived based on frequency of occurrence method. …”
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  9. 9
    Parameter identification of thermoelectric modules using enhanced slime mould algorithm (ESMA)

    Parameter identification of thermoelectric modules using enhanced slime mould algorithm (ESMA) by Ponnalagu, Dharswini, Mohd Ashraf, Ahmad, Jui, Julakha Jahan

    Published 2024
    “…Competency of the proposed algorithm in generating the optimal parameters for TEMs was appraised based on 21 benchmarked design parameters, following the objective of root mean square error (RMSE) minimization between the temperature of both actual and estimated models. …”
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  10. 10
    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
    “…The von Mises distribution is the most commonly used probability distribution of a circular random variable, and the concentration of a circular data set is measured using the mean resultant length. …”
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  11. 11
    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 algorithm also improves the calculations of shape and width of membership functions by means of clustering in order to improve the accuracy. …”
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  12. 12
    Improved robust estimator and clustering procedures for multivariate outliers detection

    Improved robust estimator and clustering procedures for multivariate outliers detection by Sharifah Sakinah, Syed Abd Mutalib

    Published 2023
    “…Therefore, many studies use robust estimators to replace the sample mean and covariance matrix. …”
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  13. 13
    Estimating the total Malaysian road accidents and fatalities using Gauss-Newton method of least squares / Maureen Giman, Siti Zulaikha Muhamad Zuraidi and Syahida Asyikin Moner

    Estimating the total Malaysian road accidents and fatalities using Gauss-Newton method of least squares / Maureen Giman, Siti Zulaikha Muhamad Zuraidi and Syahida Asyikin Moner by Giman, Maureen, Muhamad Zuraidi, Siti Zulaikha, Moner, Syahida Asyikin

    Published 2022
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  14. 14
    Robust estimation methods for fixed effect panel data model having block-concentrated outliers

    Robust estimation methods for fixed effect panel data model having block-concentrated outliers by Abu Bakar @ Harun, Nor Mazlina

    Published 2019
    “…To rectify this problem, the RWGM with RDF and RWGM with DRGP are developed by integrating the RDF and existing Diagnostic Robust Generalized Potential (DRGP); respectively, into the algorithm of GM-estimator. Results indicate that the performance of RWGM(RDF) estimator which uses RDF as part of its weighting scheme surpasses other methods under study. …”
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  15. 15
    Analysis of Probability Density Functions in Existing No-Reference Image Quality Assessment Algorithm for Contrast-Distorted Images

    Analysis of Probability Density Functions in Existing No-Reference Image Quality Assessment Algorithm for Contrast-Distorted Images by Ahmed I.T., Der C.S., Jamil N., Hammad B.T.

    Published 2023
    Conference Paper
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  16. 16
    Item Tracer

    Item Tracer by Teh , Yih Kai

    Published 2015
    “…A positioning algorithm is developed to analyse the behaviour of received signal strength and calculate the probability of the target location. …”
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    Final Year Project
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  17. 17
    Solving single and bi-objective surgery scheduling problems using local search heuristic

    Solving single and bi-objective surgery scheduling problems using local search heuristic by Ab Rashid, Nur Shafiqah

    Published 2021
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  18. 18
    Comparison of Conjugate Gradient methods for developing the multiple linear regression model for rubber yield in Malaysia / Anis Shahida Rohimi Ozeman

    Comparison of Conjugate Gradient methods for developing the multiple linear regression model for rubber yield in Malaysia / Anis Shahida Rohimi Ozeman by Rohimi Ozeman, Anis Shahida

    Published 2018
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  19. 19
    A combined-model for uncertain load and optimal configuration of distributed generation in power distribution system

    A combined-model for uncertain load and optimal configuration of distributed generation in power distribution system by Nallagownden, P., Mahesh, K., Elamvazuthi, I.

    Published 2017
    “…The uncertainties in the load are modelled by probability distribution functions (PDF) of load with Hong’s two-point estimation method. …”
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  20. 20
    A framework for automatic modelling of survival using fuzzy inference.

    A framework for automatic modelling of survival using fuzzy inference. by Hamdan, Hazlina, Garibaldi, Jonathan M.

    Published 2012
    “…After the initialisation of the fuzzy inference structure, the replication data (until time to event) will be subject to be trained using the gradient descent and nonnegative least square algorithm to estimate the conditional event probability. …”
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