Search Results - (( data estimation method algorithm ) OR ( parameter evaluation study algorithm ))
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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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2
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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Thesis -
3
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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4
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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5
Dynamic robust bootstrap method based on LTS estimators
Published 2009“…The performance of the DRBLTS is evaluated by real data sets and simulation study. The numerical examples indicate that the DRBLTS is more efficient than the other methods.…”
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6
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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Thesis -
7
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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Conference or Workshop Item -
8
A Novel Approach to Estimate Diffuse Attenuation Coefficients for QuickBird Satellite Images: A Case Study at Kish Island, the Persian Gulf.
Published 2013“…Diffuse attenuation coefficient (k d ) is a critical parameter for benthic habitat mapping using remotely sensed data. This research attempted to develop a new approach to estimate k d in blue and green bands of QuickBird satellite image based on the integration of Lyzenga’s method and updated NASA-k d 490 algorithm. …”
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9
Development Of An Automatic Calculation Method For Ct Dose Estimation Based On Individual Specific Size In Paediatric Population
Published 2022“…This study also aims to develop an automatic calculator using MATLAB algorithm for accurate patient size measurement and SSDE calculation. …”
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Thesis -
10
Field data-based mathematical modeling by Bode equations and vector fitting algorithm for renewable energy applications
Published 2018“…From the minimal RMSE, the results show clear improvements in data fitting over other methods. The most powerful features of this method is the ability to model irregular or randomly shaped data and to be applied to any algorithms that estimating models using frequency-domain data to provide state-space or transfer function for the model.…”
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Non-Parametric and Parametric Estimations of Cure Fraction Using Right-and Interval-Censored Data
Published 2011“…Then, a series of simulation studies was conducted to evaluate the performance of the proposed estimation approaches. …”
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13
Cure fraction model for interval censoring with a change point based on a covariate threshold
Published 2015“…Simulation studies were conducted to evaluate the performance of the proposed estimation method. …”
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14
Photogrammetric low-cost unmanned aerial vehicle for pothole detection mapping / Shahrul Nizan Abd Mukti
Published 2022“…For volume estimation purpose, a Digital Elevation Models (DEM) were generated from photogrammetric method with flight parameters of three (3) different camera focal length and ten (10) UAV altitude. …”
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Thesis -
15
Genetic algorithm for control and optimisation of exothermic batch process
Published 2013“…Nevertheless, these methods require huge batch of data for tuning its parameters. …”
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Thesis -
16
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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Data filtering of 5-axis inertial measurement unit using kalman filter
Published 2013“…This project endeavour to verify that the data from 5DOF IMU can be filtered using Kalman Filter method so that it can be used as an algorithm in motion alignment. …”
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Undergraduates Project Papers -
19
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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Conference or Workshop Item -
20
Interpolation and extrapolation techniques based Neural Network in estimating the missing ionospheric TEC data
Published 2024“…Normalized RMSE, RMSE and relative correction are computed for both methods to evaluate the capability of NN to interpolate and extrapolate the missing data. …”
Conference Paper
