Search Results - (( variables estimation method algorithm ) OR ( variable estimation using algorithm ))
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1
Variable block based motion estimation using hexagon diamond full search algorithm (HDFSA) via block subtraction technique
Published 2015“…There are many types of motion estimation method but the most used method is the block matching method which is the fixed block matching and the variable block matching. …”
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2
Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data
Published 2022“…The performance of the proposed method is illustrated using simulation study and on glass vessel data with 1920 variables, cardiomyopathy microarray data with 6319 variables, and octane data with 226 dimensions. …”
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3
Railway wheelset parameter estimation using signals from lateral velocity sensor
Published 2008“…The algorithm includes an instrumental variable (IV) element to reduce estimation bias and a variable forgetting factor for good parameter tracking and smooth steady state. …”
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4
Robust Estimation Methods And Outlier Detection In Mediation Models
Published 2010“…The Ordinary Least Squares (OLS) method is often use to estimate the parameters of the mediation model. …”
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5
Assessment of forest aboveground biomass estimation from superview-1 satellite image using machine learning approaches / Azinuddin Mohd Asri
Published 2022“…The suitable independent variables (hL, DBH, and CPA) were vital to estimating the dependent variable (Sc) and producing a carbon stock map for the final result. …”
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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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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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8
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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9
Use of AR Block Processing for Estimating the State Variables of Power System
Published 2008“…Samples of the local utility network for 103-bus parameter are collected and simulated using Burg and Modified Covariance algorithm to estimate the state variables. …”
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10
ADAPTIVE LINEAR ALGORITHMS FOR POWER SYSTEM FUNDAMENTAL AND HARMONIC ESTIMATION
Published 2015“…Hence, one of the objectives of this thesis is to address and enhance the introduced fundamental frequency adaptive filter method which was based on modified variable step size LMS (MVSS) algorithm using generalized square error normalized LMS algorithm. …”
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11
Sure (EM)-Autometrics: An Automated Model Selection Procedure with Expectation Maximization Algorithm Estimation Method (S/O 14925)
Published 2021“…Hence, this study concentrates on an automated model selection procedure for the SURE model by integrating the expectation-maximization (EM) algorithm estimation method, named SURE(EM)-Autometrics. …”
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Optimal parameter estimation of permanent magnet synchronous motor by using Mothflame optimization algorithm / Abdolmajid Dejamkhooy and Sajjad Asefi
Published 2018“…In the next step, the parameter identification as an optimization problem is solved by Moth-flame optimization, which is a novel nature-inspired heuristic algorithm. Simulation results and their comparison with Particle Swarm Optimization based method show high performance and good ability of the proposed method in PMSM parameter estimation.…”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…In the developed feature selection approach, multi-objective binary-valued backtracking search algorithm (MOBBSA) is used as an efficient evolutionary search algorithm to search within different combinations of input variables and selects the non-dominated feature subsets, which minimize simultaneously both the estimation error and the number of features. …”
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14
Robust remote heart rate estimation from multiple asynchronous noisy channels using autoregressive model with Kalman filter
Published 2019“…Also, it indicates that our algorithm can be used for the online environment. Finally, the application of our algorithm in search and rescue scenarios using drones is considered and an experiment is conducted to investigate the algorithm's potential to be embedded in drones.…”
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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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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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17
The Estimation of Air Temperature from NOAA/AVHRR Images and the study of NDVI-Ts impact
Published 2011“…From the brightness temperature in the images thermal bands 4&5 and using ε the surface temperature Ts was extracted using three different split-window algorithms. …”
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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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19
Neighbour-based on-demand routing algorithms for mobile ad hoc networks
Published 2017“…Accordingly, a Novel Density-Aware Routing algorithm (NDAR) is proposed. The proposed algorithm totally eliminates the need for fixed threshold values through the use of a novel formula that can easily estimate the node density and replace the fixed threshold value based on the neighbor information. …”
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20
Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari
Published 2015“…The von Mises distribution is the most commonly used probability distribution of a circular random variable, and the concentration of a circular data set is measured using the mean resultant length. …”
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