Search Results - (( _ distribution model algorithm ) OR ( parameters estimation means algorithms ))
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Accuracy enhancement for zone mapping of a solar radiation forecasting based multi-objective model for better management of the generation of renewable energy
Published 2023“…Air quality; Decision making; Forecasting; Fuzzy inference; Fuzzy neural networks; Fuzzy systems; Genetic algorithms; Inference engines; Mapping; Mean square error; Multiobjective optimization; Optimal systems; Particle swarm optimization (PSO); Quality control; Renewable energy resources; Solar radiation; Uncertainty analysis; Adaptive neuro-fuzzy inference system; ANFIS; Multi objective algorithm; Multi objective particle swarm optimization; Multi-objective genetic algorithm; Renewable energies; Renewable energy generation; Solar radiation forecasting; Parameter estimation…”
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Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares
Published 2009“…The Ordinary Least Squares (OLS) method is often used to estimate the parameters of a linear model. Under certain assumptions, the OLS estimates are the best linear unbiased estimates. …”
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Parameter-driven count time series models / Nawwal Ahmad Bukhari
Published 2018“…Simulation shows that MCEM algorithm and particle method are useful for the parameter estimation of the Poisson model. …”
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Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari
Published 2015“…This study focuses on the parameter estimation and outlier detection for some types of the circular model. …”
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5
Slice sampler algorithm for generalized pareto distribution
Published 2018“…In this paper, we developed the slice sampler algorithm for the generalized Pareto distribution (GPD) model. …”
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Estimation of Transformers Health Index Based on Condition Parameter Factor and Hidden Markov Model
Published 2023“…Electric transformers; Health; Hidden Markov models; Nonlinear programming; Probability distributions; Quality control; Viterbi algorithm; Condition parameters; Dissolved gas analysis; Distribution transformer; Emission probabilities; Health indices; Non-linear optimization; Remaining useful lives; Transition probabilities; Parameter estimation…”
Conference Paper -
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Estimation of transformers health index based on condition parameter factor and hidden Markov model
Published 2018“…Subsequently, the future states probability distribution was computed based on the HMM prediction model and viterbi algorithm was applied to find the best optimal path sequence of HI for the respective observable condition. …”
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Conference or Workshop Item -
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Parameter estimation of K-distributed sea clutter based on fuzzy inference and Gustafson-Kessel clustering
Published 2011“…This paper proposes a novel approach to estimate the parameters of K-distribution, based on fuzzy Gustafson–Kessel clustering and fuzzy Takagi–Sugeno Kang modelling. …”
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A new Gompertz-three-parameter-lindley distribution for modeling survival time data
Published 2025“…Maximum likelihood estimators (MLEs) of unknown parameters are obtained via differential evolution algorithms, and simulation studies are conducted to evaluate the consistency of the MLEs. …”
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10
Statistical approach on grading: mixture modeling
Published 2006“…In the conditional Bayesian model, we assume the data to follow the Normal Mixture distribution where the grades are distinctively separated by the parameters: means and proportions of the Normal Mixture distribution. …”
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11
Extreme air pollutant data analysis using classical and Bayesian approaches
Published 2015“…The concept of EV theory affords attention to the tails of distribution where standard models are proved unreliable. …”
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12
Parameter estimation of the cure fraction based on BCH model using left-censored data with covariates.
Published 2011“…The analysis is constructed by means of the exponential distribution in the case of left censoring and within the framework of the expectation maximization (EM) algorithm. …”
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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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14
Em Approach on Influence Measures in Competing Risks Via Proportional Hazard Regression Model
Published 2000“…From the simulation study for this particular case, we can conclude that the EM algorithm proved to be more superior in terms of mean value of parameter estimates, bias and root mean square error. …”
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15
Machine learning for mapping and forecasting poverty in North Sumatera: a datadriven approach
Published 2024“…Thus, there were three poverty clusters - low, medium, and high - that were used in the model. The best model was created using the grid search cross-validation, while the best prediction results were created using the RF algorithm, with the following parameters: n-estimator = 50, max depth = 10, min samples split = 2, and min samples leaf = 1. …”
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Channel Modeling and Direction-of-Arrival Estimation in Mobile Multiple-Antenna Communication Systems
Published 2005“…Estimated parameters from recent measurements ([PMFOO]) are compared with estimated parameters from model generated waveforms as well as theoretical distribution of received signal's angular spread. …”
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18
Statistical modelling of time series of counts for a new class of mixture distributions / Khoo Wooi Chen
Published 2016“…The statistical and regression properties, parameter estimation, forecasting, and graphical analysis for the new model have been examined. …”
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Parametric and Semiparametric Competing Risks Models for Statistical Process Control with Reliability Analysis
Published 2004“…The Expectation Maximization (EM) algorithm is utilized to obtain the estimate of the parameters in the models. …”
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20
Estimated and analysis of the relationship between the endogenous and exogenous variables using fuzzy semi-paranetric sample selection model
Published 2014“…An algorithm using the concept of fuzzy modelling is developed. …”
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