Search Results - weibull distributions ((((computer algorithm) OR (control algorithm))) OR (sensor algorithm))

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  1. 1
    Time based internet traffic policing and shaping with Weibull traffic model / Mohd Azrul Abdullah

    Time based internet traffic policing and shaping with Weibull traffic model / Mohd Azrul Abdullah by Abdullah, Mohd Azrul

    Published 2015
    “…Quality of Services for bandwidth management is a crucial task in computer network. Policing and Shaping algorithms are identified as one of the task in bandwidth control, especially in tele-traffic engineering and computer network. …”
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  2. 2
    Time based internet traffic policing and shaping with Weibull traffic model / Mohd Azrul Abdullah

    Time based internet traffic policing and shaping with Weibull traffic model / Mohd Azrul Abdullah by Abdullah, Mohd Azrul

    Published 2015
    “…Quality of Services for bandwidth management is a crucial task in computer network. Policing and Shaping algorithms are identified as one of the task in bandwidth control, especially in tele-traffic engineering and computer network. …”
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  3. 3
    Estimation Of Weibull Parameters Using Simulated Annealing As Applied In Financial Data

    Estimation Of Weibull Parameters Using Simulated Annealing As Applied In Financial Data by Hamza, Abubakar

    Published 2023
    “…The finding reveals that the Weibull distribution is well-suited to describing the investment behaviour of the MPS based on the estimates via the SA algorithm. …”
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  4. 4
    Peak time bandwidth control algorithms with fitted traffic model on broadband network YouTube video traffic: article / Aini Azmi

    Peak time bandwidth control algorithms with fitted traffic model on broadband network YouTube video traffic: article / Aini Azmi by Azmi, Aini

    Published 2016
    “…Bandwidth Control Algorithms is developed based on Peak Time of day and night. …”
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  5. 5
    Peak time bandwidth control algorithms with fitted traffic model on broadband network YouTube video traffic / Aini Azmi

    Peak time bandwidth control algorithms with fitted traffic model on broadband network YouTube video traffic / Aini Azmi by Azmi, Aini

    Published 2016
    “…Bandwidth Control Algorithms is developed based on Peak Time of day and night. …”
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  6. 6
    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
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  7. 7
    Variational Bayesian inference for exponentiated Weibull right censored survival data

    Variational Bayesian inference for exponentiated Weibull right censored survival data by Jibril Abubakar, Jibril Abubakar, Mohd Asrul Affendi Abdullah, Mohd Asrul Affendi Abdullah, Oyebayo Ridwan Olaniran, Oyebayo Ridwan Olaniran

    Published 2023
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  8. 8
    Mixture model of the Exponential, Gamma and Weibull distributions to analyse heterogeneous survival data

    Mixture model of the Exponential, Gamma and Weibull distributions to analyse heterogeneous survival data by Mohammed, Yusuf Abbakar, Yatim, Bidin, Ismail, Suzilah

    Published 2015
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  9. 9
    Parametric and Semiparametric Competing Risks Models for Statistical Process Control with Reliability Analysis

    Parametric and Semiparametric Competing Risks Models for Statistical Process Control with Reliability Analysis by Mohamed Elfaki, Faiz Ahmed

    Published 2004
    “…The study also carries out an investigation of the causes of failure for statistical process control. The x chart, R chart and Cp, and Cpk are examined for the possibility of being used to detect the state of control of the covariates in the two competing risks models (Cox’s with Weibull distribution (PHW2) and modification of weighted score function (MW)). …”
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  10. 10
    An Optimized ANN Measure-Correlate-Predict Method for Long-term Wind Prediction in Malaysia

    An Optimized ANN Measure-Correlate-Predict Method for Long-term Wind Prediction in Malaysia by Hwang Y.K., Ibrahim M.Z., Ahmed A.N., Albani A.

    Published 2023
    Conference Paper
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  11. 11
    Adaptive policing and shaping algorithms on inbound traffic using generalized Pareto distribution / Nor Azura Ayop

    Adaptive policing and shaping algorithms on inbound traffic using generalized Pareto distribution / Nor Azura Ayop by Ayop, Nor Azura

    Published 2016
    “…Log likelihood estimation technique is used to fit the best 2-parameter CDF compared to Weibull, Normal and Rician distribution model. The percentage level 5% under original bandwidth used is developed on policing and shaping algorithms to control bandwidth used. …”
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  12. 12
    Risk analysis of the copula dependent aggregate discounted claims with Weibull inter-arrival time

    Risk analysis of the copula dependent aggregate discounted claims with Weibull inter-arrival time by Siti Norafidah Mohd Ramli, Sharifah Farah Syed Yusoff Alhabshi, Nur Atikah Mohamed Rozali

    Published 2021
    “…We model the recursive moments of aggregate discounted claims, assuming the inter-claim arrival time follows a Weibull distribution to accommodate overdispersed and underdispersed data set. …”
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  13. 13
    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
    “…Two new mixed Poisson distributions, namely a three-parameter Poisson-exponentiated Weibull distribution and a fourparameter generalized Sichel distribution is introduced to model over dispersed, zeroinflated and long-tailed count data. …”
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  14. 14
    Development of warranty management visualisation for automotive aftermarket with integration of AI

    Development of warranty management visualisation for automotive aftermarket with integration of AI by Abdul Hamid, Abdul Hamid, Adull Manan, Nor Fazli, Ismail, Mohd Fauzi, Abdul Wahab, Abdul Malek, Khalit, Muhammad Ilham

    Published 2026
    “…Advanced analytics techniques including Weibull distribution modelling for failure prediction and Python based anomaly detection algorithms were implemented to identify high risk components and unusual claim behaviours. …”
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