Search Results - (( data estimation method algorithm ) OR ( data application _ algorithm ))
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1
Semiparametric inference procedure for the accelarated failure time model with interval-censored data
Published 2019“…The findings of this research provide two new iterative algorithms for estimating the parameters of the AFT model with interval-censored data, and also two new resampling techniques for estimating the covariance matrix of estimators. …”
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2
Multiple equations model selection algorithm with iterative estimation method
Published 2016“…This estimation method is equivalent to maximum likelihood estimation at convergence. …”
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3
Semiparametric estimation with profile algorithm for longitudinal binary data
Published 2013“…We use profile algorithm in the estimation of both parametric and nonparametric components. …”
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4
The development of parameter estimation method for Chinese hamster ovary model using black widow optimization algorithm
Published 2020“…It will help the researcher get the fitted graph model, correct data, and estimate the value based on the data’s behaviour. …”
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5
Pose estimation algorithm for mobile Augmented Reality based on inertial sensor fusion
Published 2021“…We evaluated the performance of augmenting the 3D object using the techniques, vision-based, and incorporating the sensor data using the video data. After extensive experiments, the validity of the proposed method was superior to the existing vision-based pose estimation algorithms. …”
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6
Utilization of canny and velocity bunching algorithms for modelling shoreline change
Published 2006“…This paper introduces new method for simulating shoreline change from multi-SAR data. …”
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7
APPLICATION OF BURG’S ALGORITHM IN STATE ESTIMATION
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8
Model selection approaches of water quality index data
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Estimation in spot welding parameters using genetic algorithm
Published 2007“…Genetic algorithm (GA) used as parameter estimation method for a model structure. …”
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10
Reduced rank technique for joint channel estimation and joint data detection in TD-SCDMA systems
Published 2013“…This situation causes mismodeling of the actual channels and introduces significant errors in the detected data of multiple users. This paper presents a novel channel estimation method with low complexity, which relies on reducing the rank order of the total channel matrix H. …”
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11
Numerical Integration And Data Reduction For Application In Photometry
Published 2003“…In this thesis, an algorithm based on a local interpolation scheme called the Average Angle Method was developed for numerical integration and data reduction of photometric data, and in general, for any data set sharing similar characteristics as the luminous intensity data The new interpolation scheme interpolates discrete data with piecewise cubic polynomials having a CI continuity in the interior. knots. …”
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12
Orthogonal least square algorithm and its application for modelling suspension system
Published 2001“…Modelling based on input and output data is known as system identification. One of the issues in system identification is the parameter estimation and model structure selection where various methods have been studied including the orthogonal least square algorithm. …”
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13
Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…This merit is provided by balancing the exploitation of solution structure and exploration of its appropriate weighting factors through use of a robust and efficient optimization algorithm in learning process of GEP approach. To assess the applicability and accuracy of the proposed method for long-term electrical energy consumption, its estimates are compared with those obtained from artificial neural network (ANN), support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), rule-based data mining algorithm, GEP, linear, quadratic and exponential models optimized by particle swarm optimization (PSO), cuckoo search algorithm (CSA), artificial cooperative search (ACS) algorithm and backtracking search algorithm (BSA). …”
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14
Simulation algorithm of bayesian approach for choice-conjoint model
Published 2011“…Therefore this research propose simulation algorithm of Bayesian approach for estimating parameter in MPM by Bayesian analysis to avoid computational difficulties in computing the maximum likelihood estimates (MLE).…”
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15
Analysis of multiexponential transient signals using interpolation-based deconvolution and parametric modeling techniques
Published 2003“…Direct deconvolution approach often leads to poor resolution of ihe estimated decay rates since the fast Fourier transform (FFT) algorithm is used to analyze the resulting deconvolved data. …”
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Proceeding Paper -
16
Parameter Estimation Using Improved Differential Evolution And Bacterial Foraging Algorithms To Model Tyrosine Production In Mus Musculus(Mouse)
Published 2015“…The hybrid of Differential Evolution algorithm with Kalman Filtering and Bacterial Foraging algorithm is a novel global optimisation method implemented to obtain the best kinetic parameter value. …”
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17
Determination of permeability characteristics of solid/liquid separation using simplex algorithm
Published 2013“…(iii) The optimum values of α1 and are searched by fitting theoretical time course of constant-pressure expression with experimental expression data by algorithm of simplex method. For efficacy evaluation of this estimation method, the permeability data of zinc oxide were determined using the method. …”
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18
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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Field data-based mathematical modeling by Bode equations and vector fitting algorithm for renewable energy applications
Published 2018“…The most powerful features of this method is the ability to model irregular or randomly shaped data and to be applied to any algorithms that estimating models using frequency-domain data to provide state-space or transfer function for the model.…”
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20
Modifying maximum likelihood test for solving singularity and outlier problems in high dimensional cases
Published 2021“…On the other hand, several shortcomings such as inconsistency under normal distribution, based on small sample size with large variables in high dimensions were discovered. To improve the ML estimators and to maintain the high breakdown point while having high dimensional data sets, a new robust estimator of banded Cholesky and L₁-median with Weiszfeld algorithm, MLѡвсн was suggested. …”
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