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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
    “…All the data for 18-bus system test are taken from previous work, and all the data for 49-bus system test are taken from an existing Iraqi distribution network. …”
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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. MTM algorithm is the new alternative in the field of Bayesian extremes for summarizing the posterior distribution. …”
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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
    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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  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
    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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  11. 11
    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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  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
    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
    “…From the results, it is known that, compared to PV only, the integration of B-SSPV plants in the distribution networks resulted in higher penetration levels in distribution networks. …”
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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
    “…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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  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
    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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  20. 20
    An Optimized Binary Scheduling Controller for Microgrid Energy Management Considering Real Load Conditions

    An Optimized Binary Scheduling Controller for Microgrid Energy Management Considering Real Load Conditions by Mannan M., Roslan M.F., Reza M.S., Mansor M., Jern K.P., Hossain M.J., Hannan M.A.

    Published 2024
    “…The proposed approach's effectiveness is evaluated within an IEEE 14-bus configuration with five microgrids (MGs) integrated with RESs using real load data from Perlis, Malaysia. The BPSO optimization technique offers an exceptional binary fitness function to find the optimal cell, utilizing real data such as solar radiation, wind speed, battery charging/discharging, fuel conditions, and demand. …”
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