Search Results - (( peer estimation methods algorithm ) OR ( parameter evaluation method algorithm ))*
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Novel chewing cycle approach for peak detection algorithm of chew count estimation
Published 2025“…These approaches were compared to the traditional All (A) chewing cycle method, which evaluates chew count across the entire dataset in a single analysis. …”
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Novel chewing cycle approach for peak detection algorithm of chew count estimation
Published 2025“…These approaches were compared to the traditional All (A) chewing cycle method, which evaluates chew count across the entire dataset in a single analysis. …”
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Kalman filter based impedance parameter estimation for transmission line and distribution line
Published 2019“…Therefore, a detailed study on developing and evaluating the new algorithms for transmission line parameter estimation is considered in this thesis. …”
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Analysis of toothbrush rig parameter estimation using different model orders in Real-Coded Genetic Algorithm (RCGA)
Published 2018“…The influence of conventional genetic algorithm parameter - generation gap has been investigated too. …”
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Estimation of photovoltaic models using an enhanced Henry gas solubility optimization algorithm with first-order adaptive damping Berndt-Hall-Hall-Hausman method
Published 2024“…A reliable methodology is essential for accurately estimating the parameters of PV models, enabling reliable performance evaluations, effective control studies, accurate analysis of partial shading effects, and optimal optimization of Photovoltaic (PV) systems. …”
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Dynamic robust bootstrap method based on LTS estimators
Published 2009“…We call this method Dynamic Robust Bootstrap-LTS based (DRBLTS) because here we have employed the LTS estimator in the modified bootstrap algorithm. …”
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Power System State Estimation In Large-Scale Networks
Published 2010“…Also the WLS algorithm is modified to include Unified Power Flow Controller (UPFC) parameters. …”
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Model selection approaches of water quality index data
Published 2016“…In order to select the best model, it is vital to ensure that proper estimation method is chosen in the modelling process.Different estimators have been proposed for the estimation of parameters of a model, including the least square and iterative estimators.This study aims to evaluate the forecasting performances of two algorithms on water quality index (WQI) of a river in Malaysia based on root mean square error (RMSE) and geometric root mean square error (GRMSE).Feasible generalised least squares (FGLS) and iterative maximum likelihood (ML) estimation methods are used in the algorithms, respectively.The results showed that SUREMLE-Autometrics has surpassed SURE-Autometrics; another simultaneous selection procedure of multipleequation models.Two individual selections, namely Autometrics-SUREMLE and Autometrics-SURE, though showed consistency only for GRMSE.All in all, ML estimation is a more appropriate method to be employed in this seemingly unrelated regression equations (SURE) model selection.…”
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Tree-based contrast subspace mining method
Published 2020“…Then, the tree-based method, the genetic algorithm based parameter values identification of tree-based method, and followed by the genetic algorithm based tree-based method, for numerical data sets are developed and evaluated. …”
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Comparison of machine learning algorithms for estimating mangrove age using sentinel 2A at Pulau Tuba, Kedah, Malaysia / Fareena Faris Francis Singaram
Published 2021“…The parameters involved to estimate the mangrove age are differences feature selection and different supervised machine learning algorithm. …”
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Restoration of blurred images using geometric and chebichef moments / Ahlad Kumar
Published 2016“…Once the blur parameters are estimated, image restoration of the proposed method is carried out using split Bregman algorithm. …”
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Parameter estimation of essential amino acids in Arabidopsis thaliana using hybrid of bees algorithm and harmony search
Published 2019“…The performance of the BAHS is evaluated and compared with other algorithms. The results show that BAHS performed better as it improved the performance of the original BA by 60%. …”
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Book Chapter -
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Position control of robot manipulator: Design a novel SISO adaptive sliding mode fuzzy PD fuzzy sliding mode control.
Published 2011“…Compare and evaluate proposed method and sliding mode algorithms under disturbance. …”
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Identification of the thermoelectric cooler using hybrid multi-verse optimizer and sine cosine algorithm based continuous-time Hammerstein model
Published 2021“…The efficiency of the proposed method is evaluated based on the convergence curve, parameter estimation error, bode plot, function plot, and Wilcoxon’s rank test. …”
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Dual-Criteria Method For Determining Critical Plane Orientation For Multiaxial Fatigue Prediction Using A Genetic Algorithm
Published 2015“…The multi-criteria-based critical plane selection method is evaluated; the considered criteria include a fatigue parameter and variance of shear stress, both maximized to find the most damaging plane. …”
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Modified multi-verse optimizer for nonlinear system identification of a double pendulum overhead crane
Published 2021“…The efficiency of the proposed HMVOSCA algorithm is evaluated using the convergence curve, parameter estimation error, bode plot, function plot, and Wilcoxon's test method. …”
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A Novel Approach to Estimate Diffuse Attenuation Coefficients for QuickBird Satellite Images: A Case Study at Kish Island, the Persian Gulf.
Published 2013“…Since the aforementioned algorithm has been developed for other types of sensors, an approach using weighted mean value of parameters for SeaWiFS, MERIS, VIIRS, and OCTS sensors were employed to estimate parameter values for QuickBird image. …”
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…The research starts with developing the hybrid deep learning model consisting of DNN and a K-Means Clustering Algorithm. Then, the developed algorithm is implemented to estimate the parameters of the Lorenz system. …”
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Scene illumination classification based on histogram quartering of CIE-Y component
Published 2014“…This method is a combination of physic based methods and data driven (statistical) methods that categorize the images based on statistical features extracted from illumination histogram of image. …”
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Thesis
