Search Results - (( data verification method algorithm ) OR ( parameter simulation study algorithm ))
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1
Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari
Published 2015“…We classify the cluster group that exceeds the stopping rule as potential outliers. Model verification of all method and model proposed in this study are examined using the simulation study. …”
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2
An enhanced motion planning method for industrial robots based on the digital twin concept
Published 2025“…The research establishes an accurate kinematic model using Denavit-Hartenberg parameters and develops an efficient simplified envelope collisiondetection method. …”
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3
Development and Application of a Finite Element Distributed Rainfall Runoff Simulation Model
Published 2000“…Maximum infiltration, overland flow discharge, and overland with channel flow discharge were observed for model verification. Finite element simulations have been shown to compare favourably with observed laboratory data. …”
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4
Stroke-to-stroke matching in on-line signature verification
Published 2010“…On-line Signature Verification is a field of verifying the time series signature data that normally obtained from the tablet-based device. …”
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5
Modelling and calibration of high-pressure direct injection compressed natural gas engine
Published 2021“…The impact of the study on the body of knowledge is a generation of a comprehensive evaluation of the HPDI-CNG configuration, which is based on analytical and data-driven model simulation and experimental testing. …”
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6
Finger vein verification system using repeated line tracking and dimensionality reduction using PCA algorithms with SURF matching
Published 2017“…The result shows that PCA can improve the accuracy of the verification system by reduce the data down into its basic component without much loss of the information…”
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Conference or Workshop Item -
7
Parameter-Less Simulated Kalman Filter
Published 2017“…Further studies on the effect of P(0), Q and R values suggest that the SKF algorithm can be realized as a parameter-less algorithm. …”
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Optimization of turning parameters using genetic algorithm method
Published 2008“…This study about development of optimization for turning parameters based on the Genetic Algorithm (GA). …”
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Undergraduates Project Papers -
9
Failure detection analysis of grid-connected photovoltaic systems in tropical climate region / Nurmalessa Muhammad @ Atan
Published 2020“…A modified threshold-based technique was used to build the FD algorithm based on data from PV system installed at GERC UiTM, Malaysia. …”
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10
A simulation based fly optimisation algorithm for swarms of mini autonomous surface vehicles application
Published 2011“…The optimal simulation parameters can be used for the real application. …”
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11
Development of android application for peninsular Malaysia GEOID height calculator / Mohamad Nazir Md Nazri
Published 2021“…Verification of algorithm of interpolation method had verified that only two interpolation methods are useable for producing results which are Bilinear Interpolation and Inverse Distance Weighted. …”
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12
Parameter estimation and outlier detection in linear functional relationship model / Adilah Abdul Ghapor
Published 2017“…This study begins by proposing a robust technique for estimating the slope parameter in LFRM. …”
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13
Estimation in spot welding parameters using genetic algorithm
Published 2007“…In this study, parameter of spot welding estimate using computer simulation. …”
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14
Optimization of milling parameters using ant colony optimization
Published 2008“…The simulation based on ACO algorithm are successful develop and the optimization of parameters values is to maximize the production rate is obtain from the simulation.…”
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Undergraduates Project Papers -
15
GENETIC ALGORITHM WITH DEEP NEURAL NETWORK SURROGATE FOR THE OPTIMIZATION OF ELECTROMAGNETIC STRUCTURE
Published 2020“…The behavior of Genetic Algorithm (GA) where it generates and evolves the parameters towards a high-quality solution gives an advantage in obtaining ideal combination of parameters to fit in with the simulation. …”
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Final Year Project -
16
The Implementation of a Machine Learning-based Routing Algorithm in a Lab-Scale Testbed
Published 2024“…Thus, researchers are developing intelligent RAs, including machine learning (ML)-based algorithms to meet traffic Q oS r equirements. However, most current studies evaluate performance using simulations. …”
Conference Paper -
17
Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm
Published 2025“…This study proposed an improved parameter estimation procedure for PEMFCs by using the GOOSE algorithm, which was inspired by the adaptive behaviours found in geese during their relaxing and foraging times. …”
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A novel architecture to verify offline hand-written signatures using convolutional neural network
Published 2023Conference Paper -
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Non-fiducial based electrocardiogram biometrics with kernel methods
Published 2017“…At classification level, Gaussian multi-class Support Vector Machine (SVM) with the One-Against-All (OAA) approach is proposed to evaluate verification performance rates of the feature extraction algorithms. …”
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20
A simulation study of a parametric mixture model of three different distributions to analyze heterogeneous survival data
Published 2013“…In this paper a simulation study of a parametric mixture model of three different distributions is considered to model heterogeneous survival data.Some properties of the proposed parametric mixture of Exponential, Gamma and Weibull are investigated.The Expectation Maximization Algorithm (EM) is implemented to estimate the maximum likelihood estimators of three different postulated parametric mixture model parameters.The simulations are performed by simulating data sampled from a population of three component parametric mixture of three different distributions, and the simulations are repeated 10, 30, 50, 100 and 500 times to investigate the consistency and stability of the EM scheme.The EM Algorithm scheme developed is able to estimate the parameters of the mixture which are very close to the parameters of the postulated model.The repetitions of the simulation give parameters closer and closer to the postulated models, as the number of repetitions increases, with relatively small standard errors.…”
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