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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
    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 difficulty with the existing rank-based methods is that they involve nonparametric estimation of the probability distribution of the model’s error terms. …”
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  3. 3
    Determination of dengue hemorrhagic fever disease factors using neural network and genetic algorithms / Yuliant Sibaroni, Sri Suryani Prasetiyowati and Iqbal Bahari Sudrajat

    Determination of dengue hemorrhagic fever disease factors using neural network and genetic algorithms / Yuliant Sibaroni, Sri Suryani Prasetiyowati and Iqbal Bahari Sudrajat by Yuliant, Sibaroni, Sri Suryani, Prasetiyowati, Iqbal Bahari, Sudrajat

    Published 2020
    “…Determination of the best factor is carried out in a genetic algorithm by combining several parameters of the crossover probability (Pc) and mutation probability (Pm). …”
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  4. 4
    Sizing and placement of solar photovoltaic plants by using time-series historical weather data

    Sizing and placement of solar photovoltaic plants by using time-series historical weather data by Ali, A., Mohd Nor, N., Ibrahim, T., Fakhizan Romlie, M.

    Published 2018
    “…In contrast to existing methods, planning for DGs by using weather data provided more realistic results for DSPP in distribution networks. …”
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  5. 5
    Sizing and placement of solar photovoltaic plants by using time-series historical weather data

    Sizing and placement of solar photovoltaic plants by using time-series historical weather data by Ali, A., Mohd Nor, N., Ibrahim, T., Fakhizan Romlie, M.

    Published 2018
    “…In contrast to existing methods, planning for DGs by using weather data provided more realistic results for DSPP in distribution networks. …”
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  6. 6
    Optimal planning of photovoltaic distributed generation considering uncertainties using monte carlo pdf embedded MVMO-SH

    Optimal planning of photovoltaic distributed generation considering uncertainties using monte carlo pdf embedded MVMO-SH by Norhafidzah, Mohd Saad

    Published 2021
    “…The proposed algorithm is applied to the standard radial test system to examine the usefulness and effectiveness of the proposed method. …”
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  7. 7
    Parameter estimation of Kumaraswamy Burr type X models based on cure models with or without covariates

    Parameter estimation of Kumaraswamy Burr type X models based on cure models with or without covariates by Yusuf, Madaki Umar

    Published 2017
    “…Kumaraswamy distribution has a closed form of probability density function (PDF) and CDF, which makes it tractable. …”
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  8. 8
    Parameter estimation of K-distributed sea clutter based on fuzzy inference and Gustafson-Kessel clustering

    Parameter estimation of K-distributed sea clutter based on fuzzy inference and Gustafson-Kessel clustering by Davari, Atefeh, Marhaban, Mohammad Hamiruce, Mohd Noor, Samsul Bahari, Karimadini, Mohammad, Karimoddini, Ali

    Published 2011
    “…K-distribution is known as the best fit probability density function for the radar sea clutter. …”
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  9. 9
    Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari

    Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari by Satari, Siti Zanariah

    Published 2015
    “…We first look at the concentration parameter of von Mises distribution. The von Mises distribution is the most commonly used probability distribution of a circular random variable, and the concentration of a circular data set is measured using the mean resultant length. …”
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  10. 10
    Optimal placement and sizing of renewable distributed generations and capacitor banks into radial distribution systems

    Optimal placement and sizing of renewable distributed generations and capacitor banks into radial distribution systems by Mahesh, K., Nallagownden, P., Elamvazuthi, I.

    Published 2017
    “…The intermittency of wind speed and solar irradiance are handled with multi-state modeling using suitable probability distribution functions. The three objective functions, i.e., power loss reduction, voltage stability improvement, and voltage deviation minimization are optimized using advanced Pareto-front non-dominated sorting multi-objective particle swarm optimization method. …”
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  11. 11
    New learning algorithm based on Hidden Markov Model (HMM) as stochastic modelling for pattern calssification

    New learning algorithm based on Hidden Markov Model (HMM) as stochastic modelling for pattern calssification by Balakrishnan, Malarvili, Ting, Chee Ming, Shaikh Salleh, Sheikh Hussain

    Published 2009
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  12. 12
    Robust Kernel Density Function Estimation

    Robust Kernel Density Function Estimation by Dadkhah, Kourosh

    Published 2010
    “…The distance of observations from the center of data set is incorporated in the formulation of the first outlier detection method in unimodal distribution. …”
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  13. 13
    Probabilistic load flow�based optimal placement and sizing of distributed generators

    Probabilistic load flow�based optimal placement and sizing of distributed generators by Hossain F.A., Rokonuzzaman M., Amin N., Zhang J., Mishu M.K., Tan W.-S., Islam M.R., Roy R.B.

    Published 2023
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  14. 14
    Sizing and placement of battery-coupled distributed photovoltaic generations

    Sizing and placement of battery-coupled distributed photovoltaic generations by Ali, A., Mohd Nor, N., Ibrahim, T., Fakhizan Romlie, M.

    Published 2017
    “…To estimate the output from PV modules, 15-year solar irradiance data is modeled using the beta probability density function. …”
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  15. 15
    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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  16. 16
    Power prediction using the wind turbine power curve and data-driven approaches / Ehsan Taslimi Renani

    Power prediction using the wind turbine power curve and data-driven approaches / Ehsan Taslimi Renani by Ehsan Taslimi , Renani

    Published 2018
    “…An alternative way to estimate the coefficients of MHTan is through maximum likelihood estimation (MLE) and the probability density function of wind speed. In this method, firstly, Weibull density function is utilized to model the wind speed and then several methods are applied to estimate the parameters of the wind speed distribution. …”
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  17. 17
    An empirical study of density and distribution functions for ant swarm optimized rough reducts

    An empirical study of density and distribution functions for ant swarm optimized rough reducts by Pratiwi, Lustiana, Choo, Yun Huoy, Draman @ Muda, Azah Kamilah

    Published 2011
    “…To describe relative probability of different random variables, Probability Density Function (PDF) and the Cumulative Density Function (CDF) are capable to specify its own characterization of Gaussian distributions. …”
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  18. 18
    A Comparative Performance Analysis of Gaussian Distribution Functions in Ant Swarm Optimized Rough Reducts

    A Comparative Performance Analysis of Gaussian Distribution Functions in Ant Swarm Optimized Rough Reducts by Pratiwi, Lustiana, Choo, Yun Huoy, Draman @ Muda, Azah Kamilah

    Published 2011
    “…Coexistence, cooperation, and individual contribution to food searching by a particle (ant) as a swarm (ant) survival behavior, depict the common characteristics of both algorithms. Solution vector of ACO is presented by implementing density and distribution function to search for a better solution and to specify a probability functions for every particle (ant). …”
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  19. 19
    Novel distributed algorithm for coalition formation for enhanced spectrum sensing in cognitive radio networks

    Novel distributed algorithm for coalition formation for enhanced spectrum sensing in cognitive radio networks by Tahir, Mohammad, Habaebi, Mohamed Hadi, Islam, Md Rafiqul

    Published 2017
    “…The utility function is defined as the average probability of false alarm per cognitive radio user. …”
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  20. 20
    Novel distributed algorithm for coalition formation in cognitive radio networks for throughput enhancement using matching theory

    Novel distributed algorithm for coalition formation in cognitive radio networks for throughput enhancement using matching theory by Tahir, Mohammad, Habaebi, Mohamed Hadi, Islam, Md Rafiqul

    Published 2017
    “…The utility function is defined as the average probability of false alarm per cognitive radio user. …”
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