Search Results - (( weibull distributions _ algorithm ) OR ( based evaluation tree algorithm ))
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Estimation Of Weibull Parameters Using Simulated Annealing As Applied In Financial Data
Published 2023“…The finding reveals that the Weibull distribution is well-suited to describing the investment behaviour of the MPS based on the estimates via the SA algorithm. …”
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Time based internet traffic policing and shaping with Weibull traffic model / Mohd Azrul Abdullah
Published 2015“…Analysis results present Weibull Distribution model is the best fitted model. …”
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Time based internet traffic policing and shaping with Weibull traffic model / Mohd Azrul Abdullah
Published 2015“…Analysis results present Weibull Distribution model is the best fitted model. …”
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Competing risks for reliability analysis using Cox’s model
Published 2007“…Purpose – Cox’s model with Weibull distribution and Cox’s with exponential distribution are the most important models in reliability analysis. …”
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Bayesian survival and hazard estimates for Weibull regression with censored data using modified Jeffreys prior
Published 2013“…For the Weibull model with right censoring and unknown shape, the full conditional distribution for the scale and shape parameters are obtained via Gibbs sampling and Metropolis-Hastings algorithm from which the survival function and hazard function are estimated. …”
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An analytical approach on parametric estimation of cure fraction based on weibull distribution using interval censored data.
Published 2011“…We propose this cure rate model based on the Weibull distribution with interval censored data. …”
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Variational Bayesian inference for exponentiated Weibull right censored survival data
Published 2023“…The Weibull distribution is on the other hand well-known for modelling monotonic hazard rates. …”
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Tree-based contrast subspace mining method
Published 2020“…The research works involve first preparing the real world numerical and categorical data sets. Then, the tree-based method, the genetic algorithm based parameter values identification of tree-based method, and followed by the genetic algorithm based tree-based method, for numerical data sets are developed and evaluated. …”
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Peak time bandwidth control algorithms with fitted traffic model on broadband network YouTube video traffic: article / Aini Azmi
Published 2016“…Bandwidth Control Algorithms is developed based on Peak Time of day and night. …”
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Peak time bandwidth control algorithms with fitted traffic model on broadband network YouTube video traffic / Aini Azmi
Published 2016“…Bandwidth Control Algorithms is developed based on Peak Time of day and night. …”
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An Optimized ANN Measure-Correlate-Predict Method for Long-term Wind Prediction in Malaysia
Published 2023“…Data mining; Genetic algorithms; Meteorology; Neural networks; Planning; Sustainable development; Weibull distribution; Climate forecasts; Measure-correlate-predict; Measurement instruments; Measurement sites; Meteorological data; Reanalysis; Weibull frequency; Wind measurement; Forecasting…”
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Laptop price prediction using decision tree algorithm / Nurnazifah Abd Mokti
Published 2024“…The project involves data collection, data preparation, and the implementation of the decision tree algorithm for price prediction. The decision tree's effectiveness and accuracy in predicting laptop prices are evaluated through rigorous testing and validation. …”
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A coalition model for efficient indexing in wireless sensor network with random mobility / Hazem Jihad Ali Badarneh
Published 2021“…The second and third scenarios evaluate the performance of Coalition-Based Index-Tree by examining the effects of Dynamic-Coalition framework and Static-Coalition algorithm on Coalition-Based Index-Tree framework. …”
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Mixture model of the Exponential, Gamma and Weibull distributions to analyse heterogeneous survival data
Published 2015“…Aims: In this study a survival mixture model of three components is considered to analyse survival data of heterogeneous nature.The survival mixture model is of the Exponential, Gamma and Weibull distributions.Methodology: The proposed model was investigated and the Maximum Likelihood (ML) estimators of the parameters of the model were evaluated by the application of the Expectation Maximization Algorithm (EM).Graphs, log likelihood (LL) and the Akaike Information Criterion (AIC) were used to compare the proposed model with the pure classical parametric survival models corresponding to each component using real survival data.The model was compared with the survival mixture models corresponding to each component.Results: The graphs, LL and AIC values showed that the proposed model fits the real data better than the pure classical survival models corresponding to each component.Also the proposed model fits the real data better than the survival mixture models corresponding to each component. …”
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Statistical modeling of the electromechanical behaviour of BI-2223 composite wires
Published 2024text::Final Year Project -
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Multiobjective optimization using particle swarm optimization with non-Gaussian random generators
Published 2016“…The two non-Gaussian distributions are the Weibull and Gamma distributions. …”
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Multiobjective optimization using particle swarm optimization with non-Gaussian random generators
Published 2016“…The two non-Gaussian distributions are the Weibull and Gamma distributions. …”
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Multiobjective optimization using particle swarm optimization with non-Gaussian random generators
Published 2016“…The two non-Gaussian distributions are the Weibull and Gamma distributions. …”
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Multiobjective optimization using particle swarm optimization with non-Gaussian random generators
Published 2016“…The two non-Gaussian distributions are the Weibull and Gamma distributions. …”
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