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  1. 1

    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
    “…Coexistence, cooperation, and individual contribution to food searching by a particle (ant) as a swarm (colony) survival behavior, depict the common characteristics of both PSO and ACO algorithms. Ant colony approach in Ant Swarm algorithm generates local solutions which satisfy the Gaussian distribution for global optimization using PSO algorithm. …”
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    Book Chapter
  2. 2

    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
    “…This paper proposed to generate solution for Particle Swarm Optimization (PSO) algorithms using Ant Colony Optimization approach, which will satisfy the Gaussian distributions to enhance PSO performance. …”
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    Article
  3. 3

    Fair bandwidth distribution marking and scheduling algorithm in network traffic classification by Al-Kharasani, Ameen Mohammed Abdulkarem

    Published 2019
    “…Finally, propose a new method of obtaining optimal parameters dropping functions for Random Early Detection (RED) algorithm. …”
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    Thesis
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    Optimal planning of photovoltaic distributed generation considering uncertainties using monte carlo pdf embedded MVMO-SH by Norhafidzah, Mohd Saad

    Published 2021
    “…A hybrid population – based stochastic optimization method named MVMO-SH algorithm is proposed to optimize PVDG locations and sizes in the grid system network. …”
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    Thesis
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    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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  9. 9

    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. The total energy loss index was formulated as the main objective function, and the optimization problem was solved by mixed integer optimization by using genetic algorithm. …”
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    Article
  10. 10

    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. The total energy loss index was formulated as the main objective function, and the optimization problem was solved by mixed integer optimization by using genetic algorithm. …”
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    Article
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    Performance Improvement of Multiobjective Optimal Power Flow-Based Renewable Energy Sources Using Intelligent Algorithm by Huy, T.H.B., Nguyen, T.P., Mohd Nor, N., Elamvazuthi, I., Ibrahim, T., Vo, D.N.

    Published 2022
    “…Weibull and lognormal probability distribution functions (PDFs) are respectively adopted to describe uncertainties in wind speed and solar irradiance. …”
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    Article
  12. 12

    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. …”
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    Article
  13. 13

    Some families of count distributions for modelling zero-inflation and dispersion / Low Yeh Ching by Low, Yeh Ching

    Published 2016
    “…The probability function of the counts is often complicated thus a method using numerical Laplace transform inversion for computing the probabilities and the renewal function is proposed. …”
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    Thesis
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    A new hybrid GA−ACO−PSO algorithm for solving various engineering design problems by Tam, Jun Hui, Ong, Zhi Chao, Ismail, Zubaidah, Ang, Bee Chin, Khoo, Shin Yee

    Published 2019
    “…The intention of this hybridization is to further enhance the exploratory and exploitative search capabilities involving simple concepts. The proposed algorithm adopts the combined discrete and continuous probability distribution scheme of ant colony optimization (ACO) to specifically assist genetic algorithm in the aspect of exploratory search. …”
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    Article
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    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. Mixed-integer optimization using a genetic algorithm is employed for solving the optimization problem. …”
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    Article
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    Determining penetration limit of central distributed generation topology in radial distribution networks by Suliman, Mohamed Saad Abdelgadir

    Published 2021
    “…On the other hand, to test the network operational limits when uncertainties of the photovoltaic generation and load demand are included, the probabilistic load flow was simulated using Monte Carlo Simulation method. The beta probability density functions were used to model the photovoltaic generation, while the normal probability density functions were used to model the load demand. …”
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    Thesis
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    Optimal performance of stand-alone hybrid microgrid systems based on integrated techno-economic-environmental energy management strategy using the grey wolf optimizer by Tukkee, Ahmed Sahib, Bin Abdul Wahab, Noor Izzri, Binti Mailah, Nashiren Farzilah, Hassan, Mohd Khair

    Published 2024
    “…The proposed strategy reduced the system’s total net present cost, power loss, and emissions by (1.06), (8.69), and (17.19), respectively compared to normal operation. Firefly Algorithm (FA) and Particle Swarm Optimization (PSO) techniques were used to verify the results. …”
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    Article
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