Search Results - re estimation method algorithm
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Segmentation of MRI brain images using statistical approaches
Published 2011“…Also, a filter-based image inhomogeneity-correction algorithm is proposed which uses the maximum filter for inhomogeneity field estimation. …”
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Kinetic parameters estimation of the Escherichia coli (E. coli) model by Garra Rufa-inspired Optimization Algorithm (GRO)
Published 2024“…As a result of this new method, it was discovered that small-scale and even whole-cell dynamic models can be estimated accurately.…”
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Robust estimation methods for fixed effect panel data model having block-concentrated outliers
Published 2019“…The Ordinary Least Squares (OLS) is the commonly used method to estimate the parameters of fixed effect panel data model. …”
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Scale-invariant and adaptive-search template matching for monocular visual odometry in low-textured environment
Published 2016“…This method is one of the most effective methods for template matching. …”
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5
Malaysia solar energy experience: intelligent fault location algorithm for unbalanced radial distribution network including PV systems
Published 2016“…The recorded values are evaluated by a designed and tuned multi-layer feed forward neural network and the fault distances from the source are estimated accordingly. In order to highlight the accuracy of the presented method, the scenario is also repeated by recording the peak values of short circuit current which have been mostly used in the published intelligent fault location studies and the obtained results via two different values are compared with each other. …”
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Robust variable selection methods for large- scale data in the presence of multicollinearity, autocorrelated errors and outliers
Published 2016“…In this situation, the existing Elastic-Net and RE-Net methods are not capable of selecting the important variables in the final model. …”
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Automated Scaling Region of Interest with Iterative Edge Preserving in Forward-Backward Time-Stepping
Published 2019“…Average RE is 61.94% for a circular shape in breast model, meanwhile attains RE of 4.17% for a U-shape object. …”
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Multi-objective optimization of stand-alone hybrid renewable energy system by genetic algorithm
Published 2013“…Among these methods, Genetic Algorithm and Particle Swarm Optimization are known as two most effective methods for HRESs. …”
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9
Improved Boosted Decision Tree Algorithms by Adaptive Apriori and Post-Pruning for Predicting Obstructive Sleep Apnea
Published 2018“…The novelty of the post-pruning technique applied is that it is augmented by AA properties and these depend on the data characteristics in the dataset(s) being accessed. This algorithm is then boosted by using AdaBoost ensemble method. …”
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Robust Kernel Density Function Estimation
Published 2010“…The classical kernel density estimation technique is the commonly used method to estimate the density function. …”
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Effect of corrugated wall combined with backward-facing step channel on fluid flow and heat transfer
Published 2020“…The governing equation was solved using Finite Volume Method (FVM) and the SIMPLE algorithm was applied to investigate the effect of backward-facing step with corrugated downstream on heat transfer characteristics. …”
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State-of-charge estimation for lithium-ion batteries with optimized self-supervised transformer deep learning model
Published 2023“…To select the optimal hyperparameters for the Transformer model, the Tree Parzen Estimator(TPE) optimization in combination with the Hyperband pruning algorithm is employed to search for the best combination that yields the lowest Root Mean Squared Error(RMSE)and Mean Absolute Error (MAE) error metrics. …”
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Energy, Vibration And Sound Research Group (e-VIBS) School Of Science And Technology Universiti Malaysia Sabah : Bioacoustics Signal Modeling Using Time-Frequency Distribution
Published 2011“…However, WSE was the best method for the RE approach with the accuracy of 92%. …”
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Pid-aco vibration controller with magnetorheological damper for wind turbine tower / Mahmudur Rahman
Published 2019“…At first, appropriate dynamic model is estimated using finite difference method (FDM) and system identification process. …”
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Optimization of Microbial Electrolysis Cell for Sago Mill Wastewater Derived Biohydrogen via Modeling and Artificial Neural Network
Published 2023“…Model validity describes the first sub-objective, which is to solve the complexity of the nonlinear interaction of multiple MEC input variables related to the hydrogen production rate response using artificial neural networks (ANN) before validating the mathematical modeling results by comparing experimental data with the predicted substrate concentration profile and hydrogen production rate profile based on the re-estimated input values of the model parameters using single-objective optimization based on the nonlinear convex method using gradient descent algorithm. …”
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Integration of filter-less unified power quality conditioner (UPQC) control scheme with solar photovoltaic and battery energy storage system / Muhammad Alif Mansor
Published 2023“…The one of most used time-domain methods in the UPQC control scheme is the synchronous reference frame (SRF). …”
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