Search Results - (( developing learning mode algorithm ) OR ( java detection method algorithm ))
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1
Real-Time Video Processing Using Native Programming on Android Platform
Published 2012“…However for the Android platform that based on the JAVA language, most of the software algorithm is running on JAVA that consumes more time to be compiled. …”
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2
Fitness value based evolution algorithm approach for text steganalysis model
Published 2013“…In this paper, we present a new alternative method for text steganalysis based on an evolution algorithm, implemented using the Java Evolution Algorithms Package (JEAP).The main objective of this paper is to detect the existence of hidden messages ased on fitness values of a text description.It is found that the detection performance has been influenced by two groups of fitness values which are good fitness value and bad fitness value. …”
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3
Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Features selection process can be considered a problem of global combinatorial optimization in machine learning. Genetic algorithm GA had been adopted to perform features selection method; however, this method could not deliver an acceptable detection rate, lower accuracy, and higher false alarm rates. …”
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4
Text steganalysis using evolution algorithm approach
Published 2012“…This study presents a new alternative of steganalysis method in order to detect hidden messages in text steganalysis called Evolution Detection Steganalysis System (EDSS) based on the evolution algorithm approach under Java Genetic Algorithms Package (JGAP). …”
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5
An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In comparison to different single algorithms for feature selection,experimental results show that the proposed ensemble method is able to reduce dimensionality, the number of irrelevant features and produce reasonable classifier accuracy. …”
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6
A multi-filter feature selection in detecting distributed denial-of-service attack
Published 2019“…In addition, the proposed M2FS method is developed through WEKA API with Java Programming language using the IDE of Eclipse Java. …”
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7
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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9
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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10
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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11
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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12
Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection
Published 2020“…The second improvement includes the development and use of new Local Search Algorithm with SSA to improve its exploitation. …”
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13
Comparative study on job scheduling using priority rule and machine learning
Published 2021“…We’ve achieved better for SJF and a decent machine learning algorithm outcome as well.…”
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14
Image clustering comparison of two color segmentation techniques
Published 2010“…There are many algorithm for analysing clustering each having its own method to do clustering. …”
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15
A malware analysis and detection system for mobile devices / Ali Feizollah
Published 2017“…We then used feature selection algorithms and deep learning algorithms to build a detection model. …”
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16
A new hybrid fuzzy ARTMAP and radial basis function neural network with online pruning strategy
Published 2023Conference Paper -
17
New Learning Models for Generating Classification Rules Based on Rough Set Approach
Published 2000“…So, the application of the theory as part of the learning models was proposed in this thesis. Two different models for learning in data sets were proposed based on two different reduction algorithms. …”
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18
An intelligent framework for modelling and active vibration control of flexible structures
Published 2004“…The work is further extended to developing and integrating the idea of active control of flexible structures into an interactive learning environment. …”
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19
Classification of imbalanced travel mode choice to work data using adjustable svm model
Published 2021“…This study deals with imbalanced mode choice data by developing an algorithm (SVMAK) based on a support vector machine model and the theory of adjusting kernel scaling. …”
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Fostering motivation in TVET students: the role of learner-paced segments and computational thinking in digital video learning
Published 2024“…Content delivered in the learner-paced mode allows students to progress through segments at their own pace, while the system-paced mode follows a fixed sequence. …”
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