Search Results - (( probable distribution function algorithm ) OR ( time estimation based algorithm ))

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  1. 1

    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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    Thesis
  2. 2

    Robust Kernel Density Function Estimation by Dadkhah, Kourosh

    Published 2010
    “…However, the weakness of IRWLS based estimator is that its computation time is very long. …”
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    Thesis
  3. 3

    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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    Thesis
  4. 4

    Tumor Extraction for Brain Magnetic Resonance Imaging Using Modified Gaussian Distribution by Salih Al-Badri, Qussay Abbas

    Published 2006
    “…The mutual information algorithms used in this work has been developed and experimented in the system and has proven to yield more accurate and stable results than other algorithms. …”
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    Thesis
  5. 5

    Fuzzy-based multi-agent approach for reliability assessment and improvement of power system protection by Nadheer Abdulridha, Shalash

    Published 2015
    “…The probability agent is to determine the capacity in service while a fuzzy model agent is to estimate the operation or failure probability. …”
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    Thesis
  6. 6

    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. …”
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    Thesis
  7. 7

    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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    Book Chapter
  8. 8

    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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    Article
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  12. 12

    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
  13. 13

    Cash-flow analysis of a wind turbine operator by Muhamad Razali N.M., Hashim A.H.

    Published 2023
    “…Two-parameter Weibull type probability density function (PDF) is used to model wind profile at two locations. …”
    Conference Paper
  14. 14

    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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    Thesis
  15. 15

    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
  16. 16

    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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    Thesis
  17. 17

    Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence by S. S. S. , Ranjit

    Published 2011
    “…There are several block-matching algorithm based on block-based motion estimation techniques have been developed. …”
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    Book Chapter
  18. 18

    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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    Article
  19. 19

    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
    “…To deal the stochastic behavior of solar irradiance, 15 years of weather data is modeled by using beta probability density function (Beta-PDF). The proposed algorithm is applied on IEEE 33 bus and IEEE 69 bus test distribution networks and optimum results are acquired for different time varying voltage dependent load models. …”
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    Book
  20. 20

    Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems by Kek, Sie Long

    Published 2011
    “…This thesis describes the development of an efficient algorithm for solving nonlinear stochastic optimal control problems in discrete-time based on the principle of model-reality differences. …”
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    Thesis