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  1. 1
    Semiparametric estimation with profile algorithm for longitudinal binary data

    Semiparametric estimation with profile algorithm for longitudinal binary data by Suliadi, Suliadi, Ibrahim, Noor Akma, Daud, Isa

    Published 2013
    “…We use profile algorithm in the estimation of both parametric and nonparametric components. …”
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  2. 2
    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
    “…The major research findings were as follows: 1) the non-parametric and parametric estimation methods using the right and interval censoring types produced highly efficient cure rate parameters when the censoring rate was decreased to the minimum possible; 2) Non-parametric estimation of the cure fraction using interval censored data based on Turnbull estimator resulted in more precise cure fraction than the Kaplan Meier estimator considering the interval midpoint to represent the exact life time; 3) The parametric estimation of the cure fraction based on the exponential distribution and right and interval censoring types produced more consistent estimates than the Weibull distribution especially in case of heavy censoring; 4) Parametric estimation of the cure fraction was more efficient when some covariates had been involved in the analysis than when covariates had been excluded; and 5) the nonparametric estimation method is the viable alternative to the parametric one when the data set contains substantial censored observations while in the case of low censoring the parametric method is more attractive.…”
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  3. 3
    Voting algorithms for large scale fault-tolerant systems

    Voting algorithms for large scale fault-tolerant systems by Karimi, Abbas

    Published 2011
    “…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. …”
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  4. 4
    Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures

    Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures by Koohi, Sina Zangbari

    Published 2020
    “…Any optimization algorithm is suitable for only a specific domain of optimization problems. …”
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  5. 5
    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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  6. 6
    Probabilistic ensemble fuzzy ARTMAP optimization using hierarchical parallel genetic algorithms

    Probabilistic ensemble fuzzy ARTMAP optimization using hierarchical parallel genetic algorithms by Loo, C.K., Liew, W.S., Seera, M., Lim, Einly

    Published 2015
    “…This was achieved by mitigating convergence in the genetic algorithms by employing a hierarchical parallel architecture. …”
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  7. 7
    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
    “…The parametric maximum likelihood estimation method was used for estimation of the cure fraction based on application of the bounded cumulative hazard (BCH) model to interval-censored data. …”
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  8. 8
    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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  9. 9
    Investigation on the dynamic of computation of semi autonomous evolutionary computation for syntactic optimization of a set of programming codes

    Investigation on the dynamic of computation of semi autonomous evolutionary computation for syntactic optimization of a set of programming codes by Mohammad Sigit Arifianto, Tze, Kenneth Kin Teo, Liau, Chung Fan, Liawas Barukang, Zaturrawiah Ali Omar

    Published 2007
    “…Genetic Algorithm as one of the Evolutionary Computation method improve the execution of parallel programming codes by optimizing the number of processors and the distribution of data. …”
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  10. 10
    Improved black-winged kite algorithm and finite element analysis for robot parallel gripper design

    Improved black-winged kite algorithm and finite element analysis for robot parallel gripper design by Haohao, Ma, As’arry, Azizan, Yanwei, Feng, Lulu, Cheng, Delgoshaei, Aidin, Ismail, Mohd Idris Shah, Ramli, Hafiz Rashidi

    Published 2024
    “…This paper presents a comprehensive study on the design optimization of a robotic gripper, focusing on both the gripper modeling and the optimization of its parallel mechanism structure. …”
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  11. 11
    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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  12. 12
    Sequential and parallel multiple tabu search algorithm for multiobjective urban transit scheduling problems

    Sequential and parallel multiple tabu search algorithm for multiobjective urban transit scheduling problems by Uvaraja, Vikneswary

    Published 2018
    “…Additionally, the MTS algorithm is also implemented in parallel computing to produce parallel MTS for generating comparable solutions in shorter computational times. …”
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  13. 13
    Analysis of evolutionary computing performance via mapreduce parallel processing architecture / Ahmad Firdaus Ahmad Fadzil

    Analysis of evolutionary computing performance via mapreduce parallel processing architecture / Ahmad Firdaus Ahmad Fadzil by Ahmad, Ahmad Firdaus

    Published 2014
    “…Examples of EC such as Genetic Algorithm (GA) and PSO (Particle Swarm Optimization) are prevalent due to their efficiency and effectiveness. …”
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  14. 14
    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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  15. 15
    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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  16. 16
    GEE-smoothing spline in semiparametric model with correlated nominal data

    GEE-smoothing spline in semiparametric model with correlated nominal data by Ibrahim, Noor Akma, Suliadi

    Published 2010
    “…We use profile algorithm in the estimation of both parametric and nonparametric components. …”
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    Conference or Workshop Item
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  17. 17
    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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  18. 18
    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 two-stage procedure is then used to estimate the EDS model parameters. Prony’s algorithm is first used to obtain initial estimates of the model, while the Gauss-Newton method is applied to solve the non-linear least-square optimisation problem. …”
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  19. 19
    Distributed parallel deep learning with a hybrid backpropagation-particle swarm optimization for community detection in large complex networks

    Distributed parallel deep learning with a hybrid backpropagation-particle swarm optimization for community detection in large complex networks by Shing, Chiang Ta, Mohammed Al-Andoli, Mohammed Nasser, Wooi, Ping Cheah

    Published 2022
    “…Next, the method is integrated with two optimization algorithms: (1) backpropagation (BP), which optimizes deep learning locally within each local chunk of the CN; (2) particle swarm optimization (PSO), which is used to improve the BP optimization involving all CN chunks. …”
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  20. 20
    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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