Search Results - based ((detection algorithm) OR (((replication algorithm) OR (selection algorithm))))
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1
Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level
Published 2024thesis::doctoral thesis -
2
A novel deadlock detection algorithm for neighbour replication on grid environment
Published 2012“…The NRGDD is compared with Multi-Cycle of Deadlock Detection and Recovery (MC2DR) algorithm based on the time required for both models to detect two deadlock cycles and using different numbers of transactions. …”
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3
A sequential handwriting recognition model based on a dynamically configurable convolution recurrent neural network and hybrid salp swarm algorithm
Published 2024“…This research present a dynamic configurator of the CRNN (DC-CRNN), geared for sequence learning in the context of handwriting recognition, inspired by bio-inspired approaches. The built DCCRNN is based on the Salp Swarm optimization Algorithm (SSA), a processor that given a particular dataset will find the best CRNN’s structure and hyperparameters. …”
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4
Artificial immune system based on real valued negative selection algorithms for anomaly detection
Published 2015“…This shows that the Negative Selection Algorithms are equipped with the capabilities of detecting changes in data, thus appropriate for anomaly detection. …”
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5
Evaluation of feature selection algorithm for android malware detection
Published 2018“…This paper synthesizes an evaluation of feature selection algorithm by utilizing Term Frequency Inverse Document Frequency (TF-IDF) as the main algorithm in Android malware detection. …”
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6
Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System
Published 2020“…Many optimisation-based intrusion detection algorithms have been developed and are widely used for intrusion identification. …”
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7
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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8
Enhanced grey wolf optimisation algorithm for feature selection in anomaly detection
Published 2022“…Thus, this study proposes an enhanced binary grey wolf optimiser (EBGWO) algorithm for FS in anomaly detection to overcome the algorithm issues. …”
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9
Edge Detection Algorithm For Image Processing Of Search And Rescue Robot
Published 2016“…Subsequently, Canny edge detection algorithm is selected as an efficient algorithm based on the comparison made and it is further used in this project. …”
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Final Year Project -
10
A comparative analysis of image copy-move forgery detection algorithms based on hand and machine-crafted features
Published 2023“…IC-MFD algorithms based hand-crafted features are the algorithms that detect the faked image depending on manual feature extraction while IC-MFD algorithms based machine-crafted features are the algorithms that detect the faked image automatically from image. …”
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11
Feature selection to enhance android malware detection using modified term frequency-inverse document frequency (MTF-IDF)
Published 2019“…This research synthesizes an evaluation of feature selection algorithm by utilizing Term Frequency-Inverse Document Frequency (TF-IDF) as the main algorithm in Android malware detection. …”
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12
Minimization of Test Cases and Fault Detection Effectiveness Improvement through Modified Reduction with Selective Redundancy Algorithm
Published 2007“…To achieve such goal, this research modifies and improves the Reduction with Selective Redundancy (RSR) algorithm. In the modify algorithm, test cases would be selected according to the branch coverage if they covered different branch combination. …”
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13
Feature Selection and Classifier Parameter Estimation for Egg Signal Peak Detection using Gravitational Search Algorithm
Published 2014“…This study focuses on using GSA method, a new computational intelligence algorithm. Moreover, a rule-based classifier is employed to distinguish a peak point based on the selected features. …”
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14
Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi
Published 2019“…Despite attempts to solve the data clustering issues, there are also many variants of modified algorithms in traditional information clustering that attempt to solve issues such as clustering algorithms based on condensation. …”
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15
Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems
Published 2022“…Most of the currently existing intrusion detection systems (IDS) use machine learning algorithms to detect network intrusion. …”
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16
Replica Creation Algorithm for Data Grids
Published 2012“…Current algorithms focus on number of accesses in deciding which file to replicate and where to place them, which ignores resources’ capabilities. …”
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17
Rao-SVM machine learning algorithm for intrusion detection system
Published 2020“…Most of the intrusion detection systems are developed based on optimization algorithms as a result of the increase in audit data features; optimization algorithms are also considered for IDS due to the decline in the performance of the human-based methods in terms of their training time and classification accuracy. …”
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18
Extremal region selection for MSER detection in food recognition
Published 2021“…Therefore, this research proposes an Extremal Region Selection (ERS) algorithm to improve MSER detection by reducing the number of irrelevant extremal regions by using unsupervised learning based on the k-means algorithm. …”
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19
Integrating genetic algorithms and fuzzy c-means for anomaly detection
Published 2005“…Clustering-based intrusion detection algorithm which trains on unlabeled data in order to detect new intrusions. …”
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20
Adaptive glioblastoma detection using evolutionary-based algorithm / Nurul Amira Mohd Ali
Published 2020“…The objectives of the project are to design and develop a prototype of adaptive Glioblastoma detection using Evolutionary-based algorithm to assist in detecting brain tumor and also to test the prototype’s functionality and detection accuracy. …”
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