Search Results - ((((regression algorithm) OR (detection algorithm))) OR (conversion algorithm))
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1
Outlier detection in circular regression model using minimum spanning tree method
Published 2019“…Therefore, this study aims to develop new algorithms that can detect outliers by using the minimum spanning tree method. …”
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2
The effect of different distance measures in detecting outliers using clustering-based algorithm for circular regression model
Published 2017“…In this study, we proposed multiple outliers detection in circular regression models based on the clustering algorithm. …”
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3
Image Processing Of Digital Mammograms For Breast Cancer Detection And Classification
Published 2018“…The accuracy of the algorithm developed in detecting tumour is 94.38% showing that it is relevant for use by radiologists. …”
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4
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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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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6
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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The effect of replacement strategies of genetic algorithm in regression test case prioritization of selected test cases
Published 2015“…This study presents an optimized regression test case prioritization of selected test cases for object-oriented software using Genetic algorithm with different replacement strategies. …”
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A New Machine Learning-based Hybrid Intrusion Detection System and Intelligent Routing Algorithm for MPLS Network
Published 2024Subjects:Article -
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Detection of multiple outliners in linear regression using nonparametric methods
Published 2004“…REFERENCES Agullo, J. (2000). New Algorithms for Computing the Least Trimmed Squares Regression Estimator. …”
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Improved intrusion detection algorithm based on TLBO and GA algorithms
Published 2021“…The proposed method combined the New Teaching-Learning-Based Optimization Algorithm (NTLBO), Support Vector Machine (SVM), Extreme Learning Machine (ELM), and Logistic Regression (LR) (feature selection and weighting) NTLBO algorithm with supervised machine learning techniques for Feature Subset Selection (FSS). …”
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11
Development of computer aided three-dimensional geometric modeler based on designer's idea in twodimensional
Published 2006“…This study has proposed better solutions in terms of an enhanced thinning algorithm, a modified Freeman chain code and Vertex chain code algorithm as picture description language, and a new computational algorithm and neural network classifier for corner detection. …”
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Capacitive sensing algorithm for elderly activity detection scheme indoor environment
Published 2018“…The detecting and tracking algorithm uses the sensory data to indicate an associated situation in order to allow elderly people with special requirements. …”
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Rao-SVM machine learning algorithm for intrusion detection system
Published 2020“…This article presents the development of an improved intrusion detection method for binary classification. In the proposed IDS, Rao Optimization Algorithm, Support Vector Machine (SVM), Extreme Learning Machine (ELM), and Logistic Regression (LR) (feature selection and weighting) were combined with NTLBO algorithm with supervised ML techniques (for feature subset selection (FSS). …”
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Single-linkage method to detect multiple outliers with different outlier scenarios in circular regression model
Published 2018“…Single-linkage is one of the algorithms in agglomerative clustering technique that can be used to detect outliers. …”
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Software regression test case prioritization for object-oriented programs using genetic algorithm with reduced-fitness severity
Published 2015“…This paper propose an optimized regression test case selection and prioritization for object-oriented software based on dependence graph model analysis of the source code and optimized the selected test case using Genetic Algorithm. …”
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16
Carbon dioxide reforming of methane over Ni-based catalysts: Modeling the effect of process parameters on greenhouse gasses conversion using supervised machine learning algorithms
Published 2023“…Catalysts; Conjugate gradient method; Learning algorithms; Methane; Multilayer neural networks; Multilayers; Sensitivity analysis; Supervised learning; Auto-regressive; Bayesian regularization; CH$-4$; Greenhouse gasse; Multilayers perceptrons; Neural-networks; Nonlinear autoregressive exogenous; Performance; Process parameters; Supervised machine learning; Carbon dioxide…”
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Alternate methods for anomaly detection in high-energy physics via semi-supervised learning
Published 2020“…In this paper, we introduce two new algorithms called EHRA and C-EHRA, which use machine learning regression and clustering to detect anomalies in samples. …”
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An analysis of intrusion detection classification using supervised machine learning algorithms on NSL-KDD dataset / Sarthak Rastogi ... [et al.]
Published 2022“…The IDS with machine learning method improves the detection accuracy of the security attacks. To this end, this paper studies the classification analysis of intrusion detection using various supervised learning algorithms such as SVM, Naive Bayes, KNN, Random Forest, Logistic Regression and Decision tree on the NSL-KDD dataset. …”
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A regression test case selection and prioritization for object-oriented programs using dependency graph and genetic algorithm
Published 2014“…This paper presents an evolutionary regression test case prioritization for object-oriented software based on dependence graph model analysis of the affected program using Genetic Algorithm. …”
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The Multiple Outliers Detection using Agglomerative Hierarchical Methods in Circular Regression Model
Published 2017“…Two agglomerative hierarchical clustering algorithms for identifying multiple outliers in circular regression model have been developed in this study. …”
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