Search Results - (( variable estimation using algorithm ) OR ( parameter estimation model algorithm ))
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Railway wheelset parameter estimation using signals from lateral velocity sensor
Published 2008“…A type of parameter estimation technique based on the linear integral filter (LIF) method, the least-absolute error with variable forgetting factor (LAE+VFF) estimation method, is proposed in this paper to estimate the railway wheelset parameters modelled as a time-varying continuous-time (C-T) system. …”
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A hybrid genetic algorithm and linear regression for prediction of NOx emission in power generation plant
Published 2023Subjects:Conference paper -
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Optimal parameter estimation of permanent magnet synchronous motor by using Mothflame optimization algorithm / Abdolmajid Dejamkhooy and Sajjad Asefi
Published 2018“…Precision of model parameters is vital in a permanent magnet synchronous motor high performance and controllability. …”
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Model selection approaches of water quality index data
Published 2016“…Automatic model selection by using algorithm can avoid huge variability in model specification process compared to manual selection.With the employment of algorithm, the right model selected is then also used for forecasting purposes. …”
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Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari
Published 2015“…Both the dependent and independent variables in the model are subjected to errors. We derive the maximum likelihood estimation of parameters as well as the variance-covariance of parameters. …”
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6
Explicit solution of parameter estimate using multiparametric programming for boost converter
Published 2023“…The parameter estimation problem is then formulated and solved using Karush-Kuhn-Tucker. …”
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Parameter estimation of multivariable system using Fuzzy State Space Algorithm / Razidah Ismail … [et al.]
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Hybrid optimization approach to estimate random demand
Published 2012“…The main objective of this study is to develop a demand forecasting model that should reflect the characteristics of random demand patterns.To accomplish this goal, a hybrid algorithm combining a genetic algorithm and a local search algorithm method was developed to overcome premature convergence in local optima problems.The performance of the hybrid algorithm was compared with a single algorithm model in estimating parameter values that minimize objective function which was used to measure the goodness-of-fit between the observed data and simulated results.However, two problems had to be overcome in the forecasting random demand model. …”
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Sediment load forecasting from a biomimetic optimization perspective: Firefly and Artificial Bee Colony algorithms empowered neural network modeling in �oruh River
Published 2025“…The hybrid model is a novel approach for estimating sediment load based on various input variables. …”
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Power System State Estimation In Large-Scale Networks
Published 2010“…The quality of estimated results will depend on the measurements, the assumed network model and its parameters. …”
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11
Robust Estimation Methods And Outlier Detection In Mediation Models
Published 2010“…Simple mediation model consists of three regression equations. The Ordinary Least Squares (OLS) method is often use to estimate the parameters of the mediation model. …”
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12
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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Hybrid fuzzy-sliding mode observer design for estimation and advanced control of an ethylene polymerization process / Jarinah Mohd Ali
Published 2017“…Observers are computational algorithms designed to estimate unmeasured state variables due to the lack of appropriate estimating devices or to replace the high-priced sensors in a plant. …”
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15
Rank regression for modeling bus dwell time in the presence of censored observations
Published 2019“…An iterative algorithm is introduced that involves a monotone estimating function of the model parameter, and its minimization is a computationally simple optimization problem. …”
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Automatic control of flotation process using computer vision
Published 2015“…A froth model correlating the image variables to process variables and a prediction system estimating the metallurgical parameters based on image variables were then developed by using a neural network structure. …”
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17
Application of genetic algorithms to model parameter identification of a recombinant e.coli high-cell density fed-batch fermentation / Kamaruddin Mamat and Farida Zuraina Mohd Yuso...
Published 2008“…In this work, a genetic algorithm was used to estimate both yield and kinetic coefficients of an unstructured model representing a fed-batch high-cell density fermentation of Escherichia coli (E. coli). …”
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Bayesian logistic regression model on risk factors of type 2 diabetes mellitus
Published 2016“…The significant variables determined by maximum likelihood method were then estimated using the BLR method. …”
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Processing time estimation in precision machining industry using AI / Lim Say Li
Published 2017“…Levenberg-Marquardt algorithm is used as the training algorithm. The results show that the data best validation performance is 7.1085 at epoch 27. …”
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20
Evaluating enhanced predictive modeling of foam concrete compressive strength using artificial intelligence algorithms
Published 2025“…Additionally, parametric and sensitivity analyses were used to assess the performance of the GPR and LR algorithms. …”
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