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  1. 1
    Semiparametric inference procedure for the accelarated failure time model with interval-censored data

    Semiparametric inference procedure for the accelarated failure time model with interval-censored data by Karimi, Mostafa

    Published 2019
    “…A computationally simple two-step iterative algorithm, called estimationapproximation algorithm, is introduced for estimating the parameters of the model on the basis of the rank estimators. …”
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  2. 2
    An enhanced segment particle swarm optimization algorithm for kinetic parameters estimation of the main metabolic model of Escherichia coli

    An enhanced segment particle swarm optimization algorithm for kinetic parameters estimation of the main metabolic model of Escherichia coli by Mohammed Adam, Kunna, Tuty Asmawaty, Abdul Kadir, Muhammad Akmal, Remli, Noorlin, Mohd Ali, Kohbalan, Moorthy, Noryanti, Muhammad

    Published 2020
    “…The results revealed that the proposed method had the ability to deal with kinetic parameters estimation in terms of time consumption and distance minimization.…”
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  3. 3
    The comparison study among optimization techniques in optimizing a distribution system state estimation

    The comparison study among optimization techniques in optimizing a distribution system state estimation by Hazim Imad, Hazim

    Published 2017
    “…This thesis introduce an intelligent decentralized State Estimation method based on Firefly algorithm for distribution power systems. …”
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  4. 4
    Some families of count distributions for modelling zero-inflation and dispersion / Low Yeh Ching

    Some families of count distributions for modelling zero-inflation and dispersion / Low Yeh Ching by Low, Yeh Ching

    Published 2016
    “…A popular distribution for the modelling of discrete count data is the Poisson distribution. …”
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  5. 5
    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
    “…Finally, the predicted and computed HI were compared to the hypothesized distribution. …”
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    Conference or Workshop Item
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  6. 6
    Automatic database of robust neural network forecasting / Saadi Ahmad Kamaruddin, Nor Azura Md. Ghani and Norazan Mohamed Ramli

    Automatic database of robust neural network forecasting / Saadi Ahmad Kamaruddin, Nor Azura Md. Ghani and Norazan Mohamed Ramli by Ahmad Kamaruddin, Saadi, Md. Ghani, Nor Azura, Mohamed Ramli, Norazan

    Published 2014
    “…Most of the previous studies seek to improve the learning algorithm of backpropagation neural networks by adapting the M-estimators predominantly. …”
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  7. 7
    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. …”
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  8. 8
    Competing risks for reliability analysis using Cox’s model

    Competing risks for reliability analysis using Cox’s model by Mohamed Elfaki, Faiz Ahmed, Daud, Isa, Ibrahim, Nor Azowa, Abdullah, M. Y., Usman, Mustofa

    Published 2007
    “…This paper seeks to show that, with a large sample size based on expectation maximization (EM) algorithm, both models give similar results. Design/methodology/approach – The parameters of the models have been estimated by method of maximum likelihood based on EM algorithm. …”
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  9. 9
    Predicting the popularity of tweets using the theory of point processes.

    Predicting the popularity of tweets using the theory of point processes. by Tan, Wai Hong

    Published 2019
    “…The MaSEPTiDE approach shows highly accurate tweet popularity predictions compared to state-of the- art approaches, especially at shorter censoring times. We further propose an inhomogeneous Poisson process model and an estimation method which utilizes internal and external knowledge, based on the times of historical retweets up to the censoring time, and the complete retweet sequences in the training data set respectively. …”
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    UMK Etheses
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  10. 10
    Robust Kernel Density Function Estimation

    Robust Kernel Density Function Estimation by Dadkhah, Kourosh

    Published 2010
    “…However, the weakness of IRWLS based estimator is that its computation time is very long. …”
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  11. 11
    Covariance matrix analysis in simultaneous localization and mapping

    Covariance matrix analysis in simultaneous localization and mapping by Nur Aqilah, Othman

    Published 2016
    “…In EKF-based SLAM, measurement data are required at each time step to complete the estimation process. …”
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  12. 12
    Density based subspace clustering: a case study on perception of the required skill

    Density based subspace clustering: a case study on perception of the required skill by Rahmat Widia, Sembiring

    Published 2014
    “…SUBCLU and DAMIRA have no un-clustered real datasets; thus the perception of the results from the cluster will produce more accurate information. The clustering time for glass dataset and liver dataset using DAMIRA method is more than 20 times longer than the FIRES, INSCY and SUBCLU, meanwhile for job satisfaction dataset, DAMIRA has the shortest time compare to SUBCLU and INSCY methods. …”
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  13. 13
    Density subspace clustering: a case study on perception of the required skill

    Density subspace clustering: a case study on perception of the required skill by Sembiring, Rahmat Widia

    Published 2014
    “…SUBCLU and DAMIRA have no un-clustered real datasets; thus the perception of the results from the cluster will produce more accurate information. The clustering time for glass dataset and liver dataset using DAMIRA method is more than 20 times longer than the FIRES, INSCY and SUBCLU, meanwhile for job satisfaction dataset, DAMIRA has the shortest time compare to SUBCLU and INSCY methods. …”
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  14. 14
    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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  15. 15
    Deep convolutional neural network processing of aerial stereo imagery to monitor vulnerable zones near power lines

    Deep convolutional neural network processing of aerial stereo imagery to monitor vulnerable zones near power lines by Qayyum, A., Saad, N.M., Kamel, N., Malik, A.S.

    Published 2018
    “…There are numerous methods of monitoring hazardous overgrowth that are expensive and time-consuming. …”
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  16. 16
    Deep convolutional neural network processing of aerial stereo imagery to monitor vulnerable zones near power lines

    Deep convolutional neural network processing of aerial stereo imagery to monitor vulnerable zones near power lines by Qayyum, A., Saad, N.M., Kamel, N., Malik, A.S.

    Published 2018
    “…There are numerous methods of monitoring hazardous overgrowth that are expensive and time-consuming. …”
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  17. 17
    Computerised Faculty Course Timetabling with Student Sectioning

    Computerised Faculty Course Timetabling with Student Sectioning by Bong, Chia Lih

    Published 2016
    “…The computational result demonstrates that proposed heul;stic algorithm outperfoJ111 current practices in all datasets. …”
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  18. 18
    Intelligent image noise types recognition and denoising system using deep learning / Khaw Hui Ying

    Intelligent image noise types recognition and denoising system using deep learning / Khaw Hui Ying by Khaw , Hui Ying

    Published 2019
    “…In order to reduce the training time and computational cost of the algorithm, Principal Components Analysis (PCA) pretraining strategy is deployed to obtain data adaptive filter banks. …”
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  19. 19
    Robust Data Fusion Techniques Integrated Machine Learning Models For Estimating Reference Evapotranspiration

    Robust Data Fusion Techniques Integrated Machine Learning Models For Estimating Reference Evapotranspiration by Chia, Min Yan

    Published 2022
    “…As for the NNE, a novel meta-learner based on the stochastic-enabled extreme learning machine integrated with whale optimisation algorithm (WOA-ELM) was developed and used in such an application for the first time. …”
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    Final Year Project / Dissertation / Thesis
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  20. 20
    Data discovery algorithm for scientific data grid environment

    Data discovery algorithm for scientific data grid environment by Abdullah, Azizol, Othman, Mohamed, Sulaiman, Md. Nasir, Ibrahim, Hamidah, Othman, Abu Talib

    Published 2005
    “…Data grid mostly deals with large computational problems and provides geographically distributed resources for large-scale data-intensive applications that generate large data sets. …”
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