Search Results - (( interval estimation methods algorithm ) OR ( variable extractions method algorithm ))
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1
Estimation of non-contact smartphone video-based vital sign monitoring using filtering and standard color conversion techniques
Published 2018“…This rPPG signal could perform better as compared to the standard vital signs estimation methods. The Inter beat interval (IBI) based on maximum peak detection approach has been used for heart rate variability estimation. …”
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2
Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm
Published 2025“…However, existing RUL prediction approaches have difficulties with variability and nonlinearity that occur during battery degradation, data extraction, feature extraction, hyperparameters optimization, and prediction model uncertainty. …”
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Semiparametric inference procedure for the accelarated failure time model with interval-censored data
Published 2019“…The rank-based methods, estimating algorithms, and resampling techniques that are developed do not involve the difficulties of the existing estimating procedures. …”
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4
Non-Parametric and Parametric Estimations of Cure Fraction Using Right-and Interval-Censored Data
Published 2011“…In this thesis, we considered two methods via the expectation maximization (EM) algorithm for cure rate estimation based on the BCH model using the two censoring types common to cancer clinical trials; namely, right and interval censoring. …”
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5
Non-parametric maximum likelihood estimation of cure fraction for interval survival data.
Published 2011“…The Nonparametric maximum likelihood estimation method is used for interval censored data based on the bounded cumulative hazard (BCH) model. …”
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6
The computation of confidence intervals for the state parameters of power systems
Published 2016“…Methods: The feasible interval estimates for the system state parameters have been modelled in this study by considering the random uncertainty in the processing measurements. …”
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7
The computation of confidence intervals for the state parameters of power systems
Published 2016“…Methods: The feasible interval estimates for the system state parameters have been modelled in this study by considering the random uncertainty in the processing measurements. …”
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8
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. Maximum likelihood estimation (MLE) method is proposed to estimate the parameters within the framework of expectation-maximization (EM) algorithm, Newton Raphson method also employed. …”
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9
Turnbull versus Kaplan-Meier estimators of cure rate estimation using interval censored data
Published 2012“…Thus, the non-parametric estimation methods are employed by means of the EM algorithm. …”
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10
Cure fraction model for interval censoring with a change point based on a covariate threshold
Published 2015“…Maximum likelihood estimators of the model parameters are obtained using the Expectation Maximization (EM) algorithm. …”
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11
Parametric maximum likelihood estimation of cure fraction using interval-censored data
Published 2013“…The parametric maximum likelihood estimation method was used for estimation of the cure fraction based on application of the bounded cumulative hazard (BCH) model to interval-censored data. …”
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12
Parametric cure fraction models for interval-censoring with a change-point based on a covariate threshold
Published 2015“…The parametric maximum likelihood estimation method is employed to verify the performance of the MCM within the framework of the expectation-maximization (EM) algorithm while the estimation methods for other models are employed in a simpler and straightforward setting. …”
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13
Rank-based inference for the accelerated failure time model in the presence of interval censored data
Published 2016“…In this paper a class of asymptotically normal rank estimators is developed which can be aquired via linear programming for estimating the parameters of the model, and a two-step iterative algorithm is introduce for solving the estimating equations. …”
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14
Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari
Published 2015“…In this study, we propose an alternative method of constructing a confidence interval based from the distribution of the estimated value of error concentration parameter obtained from the Fisher information matrix. …”
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15
Bayesian survival and hazard estimates for Weibull regression with censored data using modified Jeffreys prior
Published 2013“…The comparisons are done by using standard error and the confidence interval for maximum likelihood method and credible interval for the Bayesian method.…”
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16
Flood Routing in River Reaches Using a Three-Parameter Muskingum Model Coupled with an Improved Bat Algorithm
Published 2018“…Design of hydraulic structures, flood warning systems, evacuation measures, and traffic management require river flood routing. A common hydrologic method of flood routing is the Muskingum method. The present study attempted to develop a three-parameter Muskingum model considering lateral flow for flood routing, coupling with a new optimization algorithm namely, Improved Bat Algorithm (IBA). …”
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k- Nearest Neighbor Algorithm For Improving Accuracy In Clutter Based Location Estimation Of Wireless Nodes
Published 2013“…This research is focusing on the precise location estimation of mobile node by using k - nearest neighbor algorithm (k-NN). …”
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Voltage and load profiles estimation of distribution network using independent component analysis / Mashitah Mohd Hussain
Published 2014“…The voltage profiles are estimated for 24- hours with time interval of 1 minute. …”
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19
Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms
Published 2024“…The feature extraction methods evaluated were Grayscale Pixel Values, Mean Pixel Value of Channels, and Extracting Edge Features. …”
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Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS
Published 2017“…Since extreme learning machine is a non-iterative estimation procedure, it is faster than gradient-based algorithms which are iterative. …”
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