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  1. 1
    Non-Parametric and Parametric Estimations of Cure Fraction Using Right-and Interval-Censored Data

    Non-Parametric and Parametric Estimations of Cure Fraction Using Right-and Interval-Censored Data by Aljawdi, Bader

    Published 2011
    “…Then, a series of simulation studies was conducted to evaluate the performance of the proposed estimation approaches. …”
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  2. 2
    A parametric mixture model of three different distributions: An approach to analyse heterogeneous survival data

    A parametric mixture model of three different distributions: An approach to analyse heterogeneous survival data by Mohammed, Yusuf Abbakar, Yatim, Bidin, Ismail, Suzilah

    Published 2014
    “…A parametric mixture model of three different distributions is proposed to analyse heterogeneous survival data.The maximum likelihood estimators of the postulated parametric mixture model are estimated by applying an Expectation Maximization Algorithm (EM) scheme.The simulations are performed by generating data, sampled from a population of three component parametric mixture of three different distributions. …”
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  3. 3
    A simulation study of a parametric mixture model of three different distributions to analyze heterogeneous survival data

    A simulation study of a parametric mixture model of three different distributions to analyze heterogeneous survival data by Mohammed, Yusuf Abbakar, Yatim, Bidin, Ismail, Suzilah

    Published 2013
    “…In this paper a simulation study of a parametric mixture model of three different distributions is considered to model heterogeneous survival data.Some properties of the proposed parametric mixture of Exponential, Gamma and Weibull are investigated.The Expectation Maximization Algorithm (EM) is implemented to estimate the maximum likelihood estimators of three different postulated parametric mixture model parameters.The simulations are performed by simulating data sampled from a population of three component parametric mixture of three different distributions, and the simulations are repeated 10, 30, 50, 100 and 500 times to investigate the consistency and stability of the EM scheme.The EM Algorithm scheme developed is able to estimate the parameters of the mixture which are very close to the parameters of the postulated model.The repetitions of the simulation give parameters closer and closer to the postulated models, as the number of repetitions increases, with relatively small standard errors.…”
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  4. 4
    Non-parametric maximum likelihood estimation of cure fraction for interval survival data.

    Non-parametric maximum likelihood estimation of cure fraction for interval survival data. by I. Aljawadi, Bader Ahmad, Abu Bakar, Mohd Rizam, Ibrahim, Noor Akma

    Published 2011
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  5. 5
    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection

    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

    Published 2022
    “…The simulation is implemented with iFogSim and java programming language. …”
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  6. 6
    Parametric maximum likelihood estimation of cure fraction using interval-censored data

    Parametric maximum likelihood estimation of cure fraction using interval-censored data by Aljawadi, Bader Ahmad I., Abu Bakar, Mohd Rizam, Ibrahim, Noor Akma, Al-Omari, Mohamad

    Published 2013
    “…This paper shows derivation of the estimation equations for the cure rate parameter followed by a simulation study.…”
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  7. 7
    An intelligent framework for modelling and active vibration control of flexible structures

    An intelligent framework for modelling and active vibration control of flexible structures by Mohd. Hashim, Siti Zaiton

    Published 2004
    “…The first controller design is formulated so as to allow on-line modeling, controller design and implementation and thus, yield a self-tuning control algorithm. Performance of the AVC algorithm is assessed based on parametric design techniques, using RLS and GAS, and non-parametric design techniques, using MLP-NN and ANFIS in the suppression of vibration of the flexible structures. …”
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  8. 8
    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing

    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

    Published 2011
    “…Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources. A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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  9. 9
    Ant colony optimization algorithm for load balancing in grid computing

    Ant colony optimization algorithm for load balancing in grid computing by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

    Published 2012
    “…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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  10. 10
    Analysis of multiexponential transient signals using interpolation-based deconvolution and parametric modeling techniques

    Analysis of multiexponential transient signals using interpolation-based deconvolution and parametric modeling techniques by Salami, Momoh Jimoh Eyiomika, Ismail, Z.

    Published 2003
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  11. 11
    System Identification of XY Table ballscrew drive using parametric and non parametric frequency domain estimation via deterministic approach

    System Identification of XY Table ballscrew drive using parametric and non parametric frequency domain estimation via deterministic approach by Abdullah, Lokman, Jamaludin, Zamberi, Tsung Heng, Chiew, RAFAN, NUR AIDAWATY, syed mohamed, muhammad syafiq

    Published 2012
    “…The system for this case is XY milling table ballscrew drive. Both parametric and nonparametric procedure. In addition, comparison of estimated model transfer function obtained via non-linear least square (NLLS) and Linear least square estimator algorithm were also being addressed. …”
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  12. 12
    Semiparametric binary model for clustered survival data

    Semiparametric binary model for clustered survival data by Arlin, Rifina, Ibrahim, Noor Akma, Arasan, Jayanthi, Abu Bakar, Mohd Rizam

    Published 2014
    “…A backfitting algorithm is used in the derivation of the estimating equation for the parametric and nonparametric components of a semiparametric binary covariate model. …”
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  13. 13
    Parametric estimation of the immunes proportion based on BCH model and exponential distribution using left censored data.

    Parametric estimation of the immunes proportion based on BCH model and exponential distribution using left censored data. by I. Aljawadi, Bader Ahmad, Abu Bakar, Mohd Rizam, Ibrahim, Noor Akma, Midi, Habshah

    Published 2011
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  14. 14
    An analytical approach on parametric estimation of cure fraction based on weibull distribution using interval censored data.

    An analytical approach on parametric estimation of cure fraction based on weibull distribution using interval censored data. by I. Aljawadi , Bader Ahmad, Abu Bakar, Mohd Rizam, Ibrahim, Noor Akma

    Published 2011
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  15. 15
    Parametric and non-parametric identification of a two dimensional flexible structure

    Parametric and non-parametric identification of a two dimensional flexible structure by Mat Darus, I. Z., Tokhi, M. O.

    Published 2006
    “…The parametric approaches obtaining linear parametric models of the system using recursive least squares and genetic algorithms. …”
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  16. 16
    Analysis of the ECG signal using SVD-based parametric modelling technique

    Analysis of the ECG signal using SVD-based parametric modelling technique by Baali, Hamza, Salami, Momoh Jimoh Emiyoka, Akmeliawati, Rini, Aibinu, Abiodun Musa

    Published 2011
    “…A new parametric modeling technique for the analysis of the ECG signal is presented in this paper. …”
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  17. 17
    Evaluating enhanced predictive modeling of foam concrete compressive strength using artificial intelligence algorithms

    Evaluating enhanced predictive modeling of foam concrete compressive strength using artificial intelligence algorithms by Abdellatief M., Wong L.S., Din N.M., Mo K.H., Ahmed A.N., El-Shafie A.

    Published 2025
    “…Additionally, parametric and sensitivity analyses were used to assess the performance of the GPR and LR algorithms. …”
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  18. 18
    Estimated and analysis of the relationship between the endogenous and exogenous variables using fuzzy semi-paranetric sample selection model

    Estimated and analysis of the relationship between the endogenous and exogenous variables using fuzzy semi-paranetric sample selection model by MuhamadSafiih, L, Kamil, A.A., Abu Osman, M.T.

    Published 2014
    “…Through this approach, a flexible fuzzy concept hybrid with the semi-parametric sample selection models known as Fuzzy Semi-Parametric Sample Selection Model (FSPSSM). …”
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  19. 19
    Non-parametric induction motor rotor flux estimator based on feed-forward neural network

    Non-parametric induction motor rotor flux estimator based on feed-forward neural network by Siti Nursyuhada, Mahsahirun, Nik Rumzi, Nik Idris, Zulkifli, Md. Yusof, Sutikno, Tole

    Published 2022
    “…The conventional induction motor rotor flux observer based on current model and voltage model are sensitive to parameter uncertainties. In this paper, a non-parametric induction motor rotor flux estimator based on feed-forward neural network is proposed. …”
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  20. 20
    OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT

    OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT by Murad S.S., Badeel R., Alsandi N.S.A., Alshaaya R.F., Ahmed R.A., Muhammed A., Derahman M.

    Published 2023
    “…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. …”
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