Search Results - (( property estimation method algorithm ) OR ( parameters evaluation method algorithm ))
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Scene illumination classification based on histogram quartering of CIE-Y component
Published 2014“…Those algorithms which performed estimation carrying out lots of calculation that leads in expensive methods in terms of computing resources. …”
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Modeling and Prediction of The Mechanical Properties of Feedstock by Cooling-Slope Casting Process using MOJaya Algorithm
Published 2024“…Hence, computational methods namely the MOJaya algorithm are utilized to model and optimize the parameters of CS to address the CS problem and forecast the performance of the feedstock. …”
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Modeling and Prediction of the mechanical properties of feedstock by cooling-slope casting process using MOJaya algorithm
Published 2024“…Hence, computational methods namely the MOJaya algorithm are utilized to model and optimize the parameters of CS to address the CS problem and forecast the performance of the feedstock. …”
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Semiparametric binary model for clustered survival data
Published 2014“…The properties of the estimates for both are evaluated using simulation studies. …”
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5
On a new transmuted three-parameter lindley distribution and its applications
Published 2024“…Moreover, the maximum likelihood estimators (MLEs) of the TTHPLD are obtained via differential evolution algorithms, and a simulation study is conducted to evaluate the consistency of the MLEs. …”
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Forward-Backward Time Stepping with Automated Edge-preserving Regularization Technique for Wood Defects Detection
Published 2019“…The reconstructed images show that the algorithm was able to determine the dielectric properties within the region of interest (ROI) and estimate the shape, location of the embedded object. …”
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Nonlinear auto-regressive model structure selection using binary particle swarm optimization algorithm / Ahmad Ihsan Mohd Yassin
Published 2014“…The identification process of NARX/NARMA/NARMAX involves structure selection and parameter estimation, which can be simultaneously performed using the widely accepted Orthogonal Least Squares (OLS) algorithm. …”
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Prediction Of Petroleum Reservoir Properties Using Nonlinear Feature Selection And Ensembles Of Computational Intelligence Techniques
Published 2015“…A thorough analysis of the comparative results showed that our proposed methods and algorithms outperformed the benchmarks. …”
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On-orbit spatial image characterisation and restoration based on stochastic characteristic targets / Wong Soo Mee
Published 2021“…The experimental results demonstrate that the proposed framework is practical and effective, with < 2.3% of relative error at the Nyquist frequency as compared to the well-established edge method. In continuation of the first framework, the proposed MTF measurement algorithms are evaluated experimentally as a blur kernel estimation method for spatially varying and invariant blur removal. …”
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11
Optimization of Lipase Catalysed Synthesis of Sugar Alcohol Esters Using Taguchi Method and Neural Network Analysis
Published 2011“…The synthetic reaction was optimized by Taguchi method based on orthogonal array to evaluate the effect of each parameters and interactive effects of reaction parameters including temperature, time, amount of enzyme, amount of molecular sieve, amount of solvent, and molar ratio of substrates (xylitol: fatty acid). …”
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12
Predicting the popularity of tweets using the theory of point processes.
Published 2019“…The mode of the posterior distribution is used as the estimator of the finite-dimensional parameter, and suitable functionals of the predictive distribution for the number of retweets implied by the estimated model are used to predict the tweet popularity. …”
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Neural network based adaptive pid controller for shell-and-tube heat exchanger
Published 2019“…The dynamic behavior of the process is accurately modeled using nonlinear ARX model with 96.17% of validation accuracy and 97.5% of fit to estimation accuracy. Dynamic time series neural network model was used together with Levenberg-Marquardt algorithm as the training method. …”
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Neural network based adaptive pid controller for shell-and-tube heat exchanger: article
Published 2019“…The dynamic behavior of the process is accurately modeled using nonlinear ARX model with 96.17% of validation accuracy and 97.5% of fit to estimation accuracy. Dynamic time series neural network model was used together with Levenberg-Marquardt algorithm as the training method. …”
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Perturbation stochastic model updating of a bolted structure / Mohamad Azam Shah Aziz Shah
Published 2022“…In this study, a new scheme using the perturbation SMU method with multidimensional analysis was proposed to estimate appropriate initial values for the high-dimensional uncertain parameters in a FE model of a bolted structure. …”
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16
PATCH-IQ: A Patch Based Learning Framework For Blind Image Quality Assessment
Published 2017“…However, this approach requires an intensive training phase to optimise the regression parameters. In this paper, we overcome this limitation by proposing an alternative BIQA model that predicts image quality using nearest neighbour methods which have virtually zero training cost. …”
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Predicting the maturity and organic richness using artificial neural networks (ANNs): A case study of Montney Formation, NE British Columbia, Canada
Published 2021“…Total Organic Carbon (TOC) and maturity level (Tmax) for any source rock considered to be the key parameters for evaluating its potentiality. The TOC and Tmax are estimated mainly by analyzing core samples or cuttings using the common nonfilter acidification combustion and pyrolysis, both methods are time-consuming and costly. …”
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Gibbs excess energy model to predict phase behaviour of brine/oil/surfactant mixtures for Chemical Enhanced Oil Recovery CEOR methods
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Adaptive array antenna design for wireless communication systems
Published 2013“…In previous single-port beamforming methods, the spatial information of the signals is not fully recovered and this limits the use of conventional adaptive beamforming algorithms. …”
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Thesis
