Search Results - (( using pca learning algorithm ) OR ( java simulation optimization algorithm ))
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Anomaly detection in system log files using machine learning algorithms / Zahedeh Zamanian
Published 2019“…This study uses machine learning method to detect anomalies in system log files. …”
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…The simulation is implemented with iFogSim and java programming language. …”
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Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing
Published 2011“…Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources. A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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Ant colony optimization algorithm for load balancing in grid computing
Published 2012“…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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Modeling and validation of base pressure for aerodynamic vehicles based on machine learning models
Published 2023“…Based on the identical dataset, the GA-BP and PSO-BP algorithms are also compared to the PCA-BAS-ENN algorithm. …”
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Heart Disease Risk Prediction using Machine Learning with Principal Component Analysis
Published 2021“…The performance of the algorithms was evaluated using 10-fold cross-validation without and with Principal Component Analysis (PCA). …”
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Comparison of machine learning classifiers for dimensionally reduced fMRI data using random projection and principal component analysis
Published 2019“…In addition to that, six different types of machine learning algorithm have been used. In particular, the Haxby dataset is chosen for our experiment. …”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction
Published 2022“…This model relies mainly on dimensionality reduction and machine learning algorithms. The principal component analysis (PCA) and the linear discriminant analysis (LDA) techniques perform the dimensionality reduction in individual and hybrid modes to process and improve the data. …”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction
Published 2022“…This model relies mainly on dimensionality reduction and machine learning algorithms. The principal component analysis (PCA) and the linear discriminant analysis (LDA) techniques perform the dimensionality reduction in individual and hybrid modes to process and improve the data. …”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction
Published 2022“…This model relies mainly on dimensionality reduction and machine learning algorithms. The principal component analysis (PCA) and the linear discriminant analysis (LDA) techniques perform the dimensionality reduction in individual and hybrid modes to process and improve the data. …”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction
Published 2022“…This model relies mainly on dimensionality reduction and machine learning algorithms. The principal component analysis (PCA) and the linear discriminant analysis (LDA) techniques perform the dimensionality reduction in individual and hybrid modes to process and improve the data. …”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction
Published 2023“…This model relies mainly on dimensionality reduction and machine learning algorithms. The principal component analysis (PCA) and the linear discriminant analysis (LDA) techniques perform the dimensionality reduction in individual and hybrid modes to process and improve the data. …”
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Evaluating integrated weight linear method to class imbalanced learning in video data
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OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT
Published 2023“…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. …”
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Operational structural damage identification using de-noised modal feature in machine learning / Chen Shilei
Published 2021“…Meanwhile, the unsupervised learning method using PCA-WCC features is good at detecting unknown damage, and is sensitive to low-severity damage. …”
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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
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Feature extraction using neocognitron learning in hierarchical temporary memory
Published 2015“…Hierarchical Temporal Memory (HTM) serves as a practical implementation of the memory prediction theory.In order to obtain the optimum accuracy in pattern recognition, it is crucial to apply an appropriate learning algorithm for the feature extraction step of the HTM.This study proposes the use of neocognitron learning in extracting features of the pattern for image recognition.The integration of neocognitron into HTM addresses both the scale and time issues of the HTM. …”
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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Raspberry Pi-Based Finger Vein Recognition System Using PCANet
Published 2018“…It composed of three basic data processing components, which are PCA filter, binary hashing and histograms. PCA is employed for learning multistage filter banks. …”
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