Search Results - (( probable distribution process algorithm ) OR ( data distribution function algorithm ))

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  1. 1
    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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  2. 2
    Predictive Framework for Imbalance Dataset

    Predictive Framework for Imbalance Dataset by Megat Norulazmi, Megat Mohamed Noor

    Published 2012
    “…Experimental results suggested that the class probability distribution function of a prediction model has to be closer to a training dataset; less skewed environment enable learning schemes to discover better function F in a bigger Fall space within a higher dimensional feature space, data sampling and partition size is appear to proportionally improve the precision and recall if class distribution ratios are balanced. …”
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  3. 3
    Robust Kernel Density Function Estimation

    Robust Kernel Density Function Estimation by Dadkhah, Kourosh

    Published 2010
    “…Finally this thesis also addresses the estimation of Mutual Information (MI) for mixture distribution which prone to create two distant groups in the data. …”
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  4. 4
    Effective pilot assignment schemes in massive MIMO systems

    Effective pilot assignment schemes in massive MIMO systems by Al-Hubaishi, Ahmed Saleh Noman

    Published 2022
    “…The obtained results ensure that the proposed schemes have significantly improved the system performance in terms of achievable uplink rate and cumulative distribution function (CDF) for both SINR and uplink rate. …”
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  5. 5
    Statistical selection algorithm for peer-to-peer system

    Statistical selection algorithm for peer-to-peer system by Othman, Mohamed, Kweh, Yeah Lun

    Published 2008
    “…However, this algorithm has a high probability of failure. A few improvements have been done to this original algorithm. …”
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  6. 6
    The Distribution Network Reconfiguration Improved Performance of Genetic Algorithm Considering Power Losses and Voltage Profile

    The Distribution Network Reconfiguration Improved Performance of Genetic Algorithm Considering Power Losses and Voltage Profile by Shamsuddin, Nur Hazahsha, Omar, Nu Farhana, Sulaima, Mohamad Fani, Jaafar, Hazriq Izzuan, Abdul Kadir, Aida Fazliana

    Published 2014
    “…The SIGA algorithm was embodied throughout the process in IEEE 33-bus distribution system in selection of five tie switches. …”
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  7. 7
    Incremental learning for large-scale stream data and its application to cybersecurity

    Incremental learning for large-scale stream data and its application to cybersecurity by Ali, Siti Hajar Aminah

    Published 2015
    “…These results indi�cate that the proposed method can improve the RAN learning algorithm towards the large-scale stream data processing. …”
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  8. 8
    Enhanced Cuckoo Search Algorithm With Metaheuristic Components For Extracting The Maxima Of The Orientation Distribution Function

    Enhanced Cuckoo Search Algorithm With Metaheuristic Components For Extracting The Maxima Of The Orientation Distribution Function by Shehab, Mohammad Mohammad Said

    Published 2018
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  9. 9
    Development of heuristic methods based on genetic algorithm (GA) for solving vehicle routing problem

    Development of heuristic methods based on genetic algorithm (GA) for solving vehicle routing problem by Ismail, Zuhaimy, Nurhadi, Irhamah, Zainuddin, Zaitul Marlizawati

    Published 2008
    “…VRP in which demand at each location is unknown at the time when the route is designed but is follow a known probability distribution, is known as VRP with Stochastic Demands (VRPSD). …”
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  10. 10
    Hierarchical Bayesian estimation for stationary autoregressive models using reversible jump MCMC algorithm

    Hierarchical Bayesian estimation for stationary autoregressive models using reversible jump MCMC algorithm by Suparman, S., Rusiman, Mohd Saifullah

    Published 2018
    “…In the hierarchical Bayesian approach, the order and coefficients of the autoregressive model are assumed to have a prior distribution. The prior distribution is combined with the likelihood function to obtain a posterior distribution. …”
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  11. 11
    NSGA-III algorithm for optimizing robot collaborative task allocation in the internet of things environment

    NSGA-III algorithm for optimizing robot collaborative task allocation in the internet of things environment by Shen, jiazheng, Tang, Sai Hong, Mohd Ariffin, Mohd Khairol Anuar, As’arry, Azizan, Wang, Xinming

    Published 2024
    “…The experiment verified that this strategy can approach the optimal solution more closely during the population convergence process, and compared it with traditional Multi TSP algorithms and single function multi-objective Multi TSP algorithms. …”
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  12. 12
    Improvement and performance analysis on statistical selection algorithms

    Improvement and performance analysis on statistical selection algorithms by Kweh, Yeah Lun, Othman, Mohamed

    Published 2006
    “…However, this algorithm has a high probability of failure. A few improvements have been done to this original algorithm. …”
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  13. 13
    A maintenance cost study of transformers based on markov model utilizing frequency of transition approach

    A maintenance cost study of transformers based on markov model utilizing frequency of transition approach by Yahaya M.S., Azis N., Selva A.M., Kadir M.Z.A.A., Jasni J., Kadim E.J., Hairi M.H., Ghazali Y.Z.Y.

    Published 2023
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  14. 14
    Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets

    Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets by Saeed, Sana

    Published 2019
    “…Thereafter, a multi-objective hybrid algorithm (MOHA), an extension of the self-adaptive hybrid algorithm is proposed and tested on the established multi-objective (MO) test functions. …”
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  15. 15
    A new Gompertz-three-parameter-lindley distribution for modeling survival time data

    A new Gompertz-three-parameter-lindley distribution for modeling survival time data by Liang, Fei, Lu, Hezhi, Xi, Yuhang

    Published 2025
    “…The statistical properties of the proposed distribution including the shape properties, cumulative distribution, quantile functions, moment generating function, failure rate function, mean residual function, and stochastic orders are studied. …”
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  16. 16
    Reliability Analysis and Prediction of Time to Failure Distribution of an Automobile Crankshaft

    Reliability Analysis and Prediction of Time to Failure Distribution of an Automobile Crankshaft by Salvinder Singh, Karam Singh, Shahrum, Abdullah, Nik Abdullah, Nik Mohamed

    Published 2015
    “…The developed stochastic algorithm has the capability to measure the parametric distribution function and validate the predict the reliability rate, mean time to failure and hazard rate. …”
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  17. 17
    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
    “…The main contribution of this research is developing statistical approaches, and introducing new algorithms and resampling methods for analysing interval-censored data through AFT models.…”
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  18. 18
    Slice sampler algorithm for generalized pareto distribution

    Slice sampler algorithm for generalized pareto distribution by Rostami, Mohammad, Adam, Mohd Bakri, Yahya, Mohamed Hisham, Ibrahim, Noor Akma

    Published 2018
    “…In this paper, we developed the slice sampler algorithm for the generalized Pareto distribution (GPD) model. …”
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  19. 19
    Parallel algorithms for numerical simulations of EHD ion-drag micropump on distributed parallel computing systems

    Parallel algorithms for numerical simulations of EHD ion-drag micropump on distributed parallel computing systems by Shakeel Ahmed, Kamboh

    Published 2014
    “…In order to evaluate the scalability at specific data size the appropriate regression models are fitted through the measured data as functions of number of workers. …”
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  20. 20
    Parameter-driven count time series models / Nawwal Ahmad Bukhari

    Parameter-driven count time series models / Nawwal Ahmad Bukhari by Nawwal , Ahmad Bukhari

    Published 2018
    “…A key property of our model is that the distributions of the observed count data are independent, conditional on the latent process, although the observations are correlated marginally. …”
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