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  1. 1
    Network reconfiguration and control for loss reduction using genetic algorithm

    Network reconfiguration and control for loss reduction using genetic algorithm by Jawad, Mohamed Hassan Izzaldeen

    Published 2010
    “…In this work a feeder reconfiguration algorithm is presented for the purpose of power loss reduction in distribution networks. …”
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  2. 2
    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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  3. 3
    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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  4. 4
    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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  5. 5
    Optimal network reconfiguration and intelligent service restoration prediction technique based on Cuckoo search spring algorithm / Mohamad Izwan Zainal

    Optimal network reconfiguration and intelligent service restoration prediction technique based on Cuckoo search spring algorithm / Mohamad Izwan Zainal by Zainal, Mohamad Izwan

    Published 2022
    “…In addition, objective function using the same CSSA algorithm were applied i.e., Vmin and Ploss as the objective function, and multi-objective involves Vmin and Ploss as the objective function. …”
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  6. 6
    Bayesian inference for the bivariate extreme model

    Bayesian inference for the bivariate extreme model by Mohd Amin, Nor Azrita, Adam, Mohd Bakri

    Published 2016
    “…Maximum likelihood method and a Markov chain Monte Carlo (MCMC) technique, Multiple-try Metropolis algorithm are implemented into the data analysis. …”
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  7. 7
    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
    “…Empirical cumulative distribution function (CDF) model is presented in evaluating the real traffic distribution. …”
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  8. 8
    Optimal coordinated voltage control in active distribution networks using backtracking search algorithm

    Optimal coordinated voltage control in active distribution networks using backtracking search algorithm by Hashim T.J.T., Mohamed A.

    Published 2023
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  9. 9
    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
    “…To predict the output from the PV modules, 15 years of solar data were modeled with the aid of a beta probability density function. …”
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  10. 10
    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
    “…To predict the output from the PV modules, 15 years of solar data were modeled with the aid of a beta probability density function. …”
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  11. 11
    Sizing and Placement of Battery-Sourced Solar Photovoltaic (B-SSPV) Plants in Distribution Networks

    Sizing and Placement of Battery-Sourced Solar Photovoltaic (B-SSPV) Plants in Distribution Networks by Ali, A., Nor, N.M., Ibrahim, T., Romlie, M.F., Bingi, K.

    Published 2021
    “…This chapter proposes a mixed-integer optimization using genetic algorithm (MIOGA) for determining the optimum sizes and placements of battery-sourced solar photovoltaic (B-SSPV) plants to reduce the total energy losses in distribution networks. …”
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  12. 12
    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
    “…Empirical cumulative distribution function (CDF) model is presented in evaluating the real traffic distribution. …”
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  13. 13
    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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  14. 14
    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
    “…Also, a one-step iterative algorithm, called expected rank algorithm, is introduced which is more complicated than the estimation-approximation algorithm, but more accurate. …”
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  15. 15
    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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  16. 16
    An experience oriented-convergence improved gravitational search algorithm for minimum variance distortionless response beamforming optimum

    An experience oriented-convergence improved gravitational search algorithm for minimum variance distortionless response beamforming optimum by Darzi S., Tiong S.K., Tariqul Islam M., Rezai Soleymanpour H., Kibria S.

    Published 2023
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  17. 17
    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
    “…In this study, the problem of determination dengue disease factors was modeled using a neural network. The activation function in this neural network model then estimated using genetic algorithms. …”
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  18. 18
    Solving economic load dispatch problem using genetic algorithm method / Norliza Kamarulzaman

    Solving economic load dispatch problem using genetic algorithm method / Norliza Kamarulzaman by Kamarulzaman, Norliza

    Published 2009
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  19. 19
    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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  20. 20
    Not seeing the forest for the trees: Generalised linear model out-performs random forest in species distribution modelling for Southeast Asian felids

    Not seeing the forest for the trees: Generalised linear model out-performs random forest in species distribution modelling for Southeast Asian felids by Chiaverini, Luca, Macdonald, David W., Hearn, Andrew J., Kaszta, Zaneta, Ash, Eric, Bothwell, Helen M., Can, Ozgun Emre, Channa, Phan, Clements, Gopalasamy Reuben *, Haidir, Iding Achmad, Kyaw, Pyae Phyoe, Moore, Jonathan H., Rasphone, Akchousanh, Tan, Cedric Kai Wei, Cushman, Samuel A.

    Published 2023
    “…Species Distribution Models (SDMs) are a powerful tool to derive habitat suitability predictions relating species occurrence data with habitat features. …”
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