Search Results - (( data detection method algorithm ) OR ( parameter simulation model algorithm ))
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1
Comparative study of clustering-based outliers detection methods in circular-circular regression model
Published 2021“…This paper is a comparative study of several algorithms for detecting multiple outliers in circular-circular regression model based on the clustering algorithms. …”
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2
Comparative study of clustering-based outliers detection methods in circular-circular regression model
Published 2021“…This paper is a comparative study of several algorithms for detecting multiple outliers in circular-circular regression model based on the clustering algorithms. …”
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3
Comparative study of clustering-based outliers detection methods in circularcircular regression model
Published 2021“…This paper is a comparative study of several algorithms for detecting multiple outliers in circular-circular regression model based on the clustering algorithms. …”
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4
Fraud detection in telecommunication using pattern recognition method / Mohd Izhan Mohd Yusoff
Published 2014“…The new algorithm is tested on simulated and real data where the results show it is capable of detecting fraud activities. …”
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5
Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari
Published 2015“…This study focuses on the parameter estimation and outlier detection for some types of the circular model. …”
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6
Road damage detection for autonomous driving vehicles using YOLOv8 and salp swarm algorithm
Published 2025“…Consequently, this paper proposes a method to improve the detection accuracy of You Only Look Once version 8 (YOLOv8) using Salp Swarm Algorithm (SSA) for hyperparameter optimization, focusing on eight key parameters. …”
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Parameter estimation of multicomponent transient signals using deconvolution and ARMA modelling techniques
Published 2003“…In this method of analysis the exponential signal is converted to a convolution model whose input is a train of weighted delta function that contains the signal parameters to be determined.The resolution of the estimated decay rates is poor if the conventional fast Fourier transform (FFT) algorithm is used to analyse the resulting deconvolved data. …”
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Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares
Published 2009“…The Ordinary Least Squares (OLS) method is often used to estimate the parameters of a linear model. …”
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9
Defect recognition method for magnetic leakage detection in oil and gas steel pipes based on improved neural networks / Wang Jie ... [et al.]
Published 2024“…Simulated data are generated using ANSYS software by using models of semi-circular defects in steel pipes, producing magnetic leakage signals of varying intensities. …”
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Defect recognition method for magnetic leakage detection in oil and gas steel pipes based on improved neural networks
Published 2024“…Simulated data are generated using ANSYS software by using models of semi-circular defects in steel pipes, producing magnetic leakage signals of varying intensities. …”
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Vision-Based Autonomous Vehicle Driving Control System
Published 2005“…The important contribution of this study is the development of vehicle lane detection and tracking algorithm based on colour cue segmentation, Canny edge detection and Hough transform. …”
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12
Vision-based autonomous vehicle driving control system
Published 2005“…The important contribution of this study is the development of vehicle lane detection and tracking algorithm based on colour cue segmentation, Canny edge detection and Hough transform. …”
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13
A simple model-free butterfly shape-based detection (BSD) method integrated with deep learning CNN for valve stiction detection and quantification
Published 2020“…This simple model-free butterfly shape-based detection (BSD) method uses Stenman's one parameter stiction model, which results in a distinctive â��butterflyâ�� pattern in the presence of stiction. …”
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14
Em Approach on Influence Measures in Competing Risks Via Proportional Hazard Regression Model
Published 2000“…From the simulation study for this particular case, we can conclude that the EM algorithm proved to be more superior in terms of mean value of parameter estimates, bias and root mean square error. …”
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15
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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16
Modelling of intelligent intrusion detection system: making a case for snort
Published 2018“…Hence, this study proposes a method for early detection of an intrusion by using Snort software. …”
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Proceeding Paper -
17
Embedded fuzzy classifier for detection and classification of preseizure state using real EEG data
Published 2014“…In order to make all this in a ubiquitous form factor, the algorithm for classification and detection of the pre-seizure conditions should be tremendously simple for processing the signal in a low cost ubiquitous microcontroller. …”
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Integrated geophysical, hydrogeochemical and artificial intelligence techniques for groundwater study in the Langat Basin, Malaysia / Mahmoud Khaki
Published 2014“…These results confirm that, for all the networks the Levenberg-Marquardt algorithm is the most effective algorithm to model the groundwater level. …”
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19
Analysis of WiMAX Positioning Using Received- Signal-Strength Method
Published 2013“…With this simulator, the user can specify their own data or parameters in analyzing and obtaining the target object location. …”
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Robust Estimation Methods And Outlier Detection In Mediation Models
Published 2010“…When the relationship between the dependent variable (DV) and an independent variables (IV) can be accounted for by an intermediate variable M, mediation is said to occur. Simple mediation model consists of three regression equations. The Ordinary Least Squares (OLS) method is often use to estimate the parameters of the mediation model. …”
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