Search Results - (( data detection method algorithm ) OR ( based 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
Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data
Published 2022“…The proposed algorithm has been applied to detect outliers in the high dimensional data. …”
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5
Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification
Published 2011“…Identification studies using NARX (Nonlinear AutoRegressive with eXogenous input) models employing simulated systems and real plant data are used to demonstrate that the algorithm is able to detect significant variables and terms faster and to select a simpler model structure than other well-known EC methods.…”
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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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7
Development of a rule-based fault diagnostic advisory system for precut fractionation column
Published 2005“…The advisory system algorithm used process history based method and presented by rule-based approach. …”
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8
Detection of multiple outliners in linear regression using nonparametric methods
Published 2004“…Generally, method proposed by Sebert et al. (1998) is based on the use of single linkage clustering algorithm with the Euclidean distances to cluster the points in the plots of standard predicted versus residuals values from a linear regression model. …”
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Monograph -
9
Test case generation from state machine with OCL constraints using search-based techniques / Aneesa Ali Ali Saeed
Published 2017“…The existing infeasible path detection methods are restricted to extended finite state machine (EFSM) models with integer data type only. …”
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10
Fault diagnostic algorithm for precut fractionation column
Published 2004“…The fault diagnostic algorithm is supported by the process history based method and developed by using Borland C++ Builder 6.0. …”
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11
Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares
Published 2009“…We modified the classical bootstrapping algorithm by developing a mechanism based on the robust LTS method to detect the correct number of outliers in the each bootstrap sample. …”
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12
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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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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Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari
Published 2015“…Later, we assess the performance of confidence interval for error concentration parameter for the new functional relationship model via simulation study. Lastly, we consider the problem of detecting multiple outliers in circular regression models based on the clustering algorithm. …”
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15
Survival modelling, missing values and frailty with application to cervical cancer data / Nuradhiathy Abd Razak
Published 2016“…Overall, the EM algorithm by method of weight performs well compared to other methods. …”
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16
Development of fault detection, diagnosis and control system identification using multivariate statistical process control (MSPC)
Published 2006“…The present fault detection and diagnosis (FDD) method based on MSPC uses statistical control charts and contribution plots. …”
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Monograph -
17
Intrusion Detection in Mobile Ad Hoc Networks Using Transductive Machine Learning Techniques
Published 2011“…This research investigates the use of a promising technique from machine learning to designing the most suitable intrusion detection for this challenging network type. The proposed algorithm employs a combined model that uses two different measures (nonconformity metric measures and Local Distance-based Outlier Factor (LDOF)) to improve its detection ability. …”
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18
Development of optimized damage prediction method for health monitoring of ultra high performance fiber-reinforced concrete communication tower
Published 2018“…The results are used to develop the hybrid learning algorithm based on the AdaBoost, Bagging, and RUSBoost methods to predict the damage in the tower based on dynamic frequency domain. …”
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19
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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20
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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