Search Results - (( model estimation modeling algorithm ) OR ( time estimation based algorithm ))*
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1
Semiparametric inference procedure for the accelarated failure time model with interval-censored data
Published 2019“…A computationally simple two-step iterative algorithm, called estimationapproximation algorithm, is introduced for estimating the parameters of the model on the basis of the rank estimators. …”
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Thesis -
2
LASSO-type estimations for threshold autoregressive and heteroscedastic time series models.
Published 2020“…In this thesis, we propose Least Absolute Shrinkage and Selection Operator (LASSO) type estimators to perform simultaneous parameter estimation and model selection for five specific univariate and multivariate time series models, and develop several algorithms to compute these estimators. …”
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UMK Etheses -
3
Parameter estimation of cocomo model using the jaya algorithm for software cost estimation
Published 2019“…This thesis proposed the Jaya algorithm based on estimation of the software based on the COCOMO I model. …”
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Undergraduates Project Papers -
4
Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems
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 -
5
An enhanced segment particle swarm optimization algorithm for kinetic parameters estimation of the main metabolic model of Escherichia coli
Published 2020“…In addition, building a kinetic model requires the estimation of the kinetic parameters, but kinetic parameters estimation in kinetic modeling is a difficult task due to the nonlinearity of the model. …”
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Article -
6
Identification of the thermoelectric cooler using hybrid multi-verse optimizer and sine cosine algorithm based continuous-time Hammerstein model
Published 2021“…This paper presents the identification of the ThermoElectric Cooler (TEC) plant using a hybrid method of Multi-Verse Optimizer with Sine Cosine Algorithm (hMVOSCA) based on continuous-time Hammerstein model. …”
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Article -
7
Estimation of Response Transfer Functions of Offshore Structures Using the Time-Varying ARX Model
Published 2013“…The approach is based on time-varying autoregressive with exogenous input (TVARX) model. …”
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Conference or Workshop Item -
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Analysis of toothbrush rig parameter estimation using different model orders in Real-Coded Genetic Algorithm (RCGA)
Published 2018“…Generation gap used was 0.5 has shorten the algorithm convergence time without affecting the model accuracy.…”
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Article -
10
Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence
Published 2011“…There are several block-matching algorithm based on block-based motion estimation techniques have been developed. …”
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Book Chapter -
11
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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Article -
12
An adaptive block-based matching algorithm for crowd motion sequences
Published 2018“…The proposed algorithm is based on block-based matching, particle advection, and social force model. …”
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Article -
13
An adaptive block-based matching algorithm for crowd motion sequences
Published 2018“…The proposed algorithm is based on block-based matching, particle advection, and social force model. …”
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Article -
14
Thermoelectric cooler identification based on continuous-time hammerstein model using metaheuristics algorithm
Published 2021“…The results demonstrate that the proposed hMVOSCA algorithm can produce the Hammerstein model that generates an estimated output like the actual TEC output. …”
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Conference or Workshop Item -
15
SLOW DRIFT MOTIONS IDENTIFICATION OF FLOATING STRUCTURES USING TIME-VARYING INPUT -OUTPUT MODELS
Published 2015“…Three steps of improvements had been made to increase the modeling capacity of input-output models. The first step is presenting the backward estimator and combined forward-backward estimator instead of the only forward estimator in the original input-output models; the second step is reformulating the input-output models into a state-space model so that the Kalman Smoother (KS) adaptive filter can be used to estimate the model coefficients; the third step is optimization of KS parameters using evolutionary computing algorithms such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Artificial Bee Colony (ABC) to form the PSO-KS, GA-KS and ABC-KS as estimation methods.…”
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Thesis -
16
Multilevel optimization for dense motion estimation
Published 2011“…Experimental results on three image sequences using four models of optical flow with different computational efforts show that the FMG/Opt algorithm outperforms significantly both the TN and MR/Opt algorithms in terms of the computational work and the quality of the optical flow estimation.…”
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Monograph -
17
Performance of MIMO space-time coded system and training based channel estimation for MIMO-OFDM system
Published 2006“…Firstly it has investigated the performance of MIMO-STBC system and surveyed the effect of imperfect channel estimation on performance of MIMO-OFDM system. Secondly, it has focused on training based channel estimation algorithm for MIMO-OFDM system. …”
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Thesis -
18
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 -
19
Analysis of Toothbrush Rig Parameter Estimation Using Different Model Orders in Real Coded Genetic Algorithm (RCGA)
Published 2024“…Generation gap used was 0.5 has shorten the algorithm conver-gence time without affecting the model accuracy.…”
Article -
20
Improved recurrent NARX neural network model for state of charge estimation of lithium-ion battery using pso algorithm
Published 2023“…Backpropagation; Charging (batteries); Errors; Industrial electronics; Ions; Lithium-ion batteries; Mean square error; Particle swarm optimization (PSO); Recurrent neural networks; Temperature; Back-propagation neural networks; Drive cycles; Lithium ions; NARX neural network; Nonlinear AutoRegressive with eXogenous input models; Particle swarm optimization algorithm; State of charge; State-of-charge estimation; Battery management systems…”
Conference Paper
