Search Results - (( java implication _ algorithm ) OR ( based detection ((method algorithm) OR (bees algorithm)) ))
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An efficient intrusion detection model based on hybridization of artificial bee colony and dragonfly algorithms for training multilayer perceptrons
Published 2020“…This study proposes a new binary classification model for intrusion detection, based on hybridization of Artificial Bee Colony algorithm (ABC) and Dragonfly algorithm (DA) for training an artificial neural network (ANN) in order to increase the classification accuracy rate for malicious and non-malicious traffic in networks. …”
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Hybrid Artificial Bee Colony Algorithm for t-Way Interaction Test Suite Generation
Published 2019“…This is called hybrid artificial bee colony (HABC) strategy, which is based on hybridize of an artificial bee colony (ABC) algorithm with a particle swarm optimization (PSO) algorithm. …”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications
Published 2025“…Accordingly, the aim of this study is to identify the latest SQL injection attacks based on user’s inputs in web application associated with remote server database, and to develop a new method based on dynamic detection technique to prevent SQL injection attacks. …”
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Metaheuristic based ids using multi-objective wrapper feature selection and neural network classification
Published 2021“…The classifier, named as HADMLP is trained using a hybridization of the artificial bee colony along with the dragonfly algorithm. A multi-objective artificial bee colony model which is wrapper-based is used for selection of feature. …”
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Optimal distributed generation and load shedding scheme using artificial bee colony- hill climbing algorithm considering voltage stability and losses indices
Published 2021“…The proposed solution is based on the optimization method developed from a combination of the Artificial Bee Colony and Hill Climbing algorithms (ABC-HC) to give the optimal placement and sizing of DG units to be deployed in the system. …”
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Thesis -
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Exploration and Exploitation Mechanism in Pairwise Test Case Generation: A Systematic Literature Review
Published 2025“…Covering research from 2014 to 2024, the review evaluates hybrid and metaheuristic strategies, including Pairwise Migrating Birds Optimization-Based Strategies (PMBOS), Pairwise Gravitational Search Algorithm Strategy (PGSAS), Pairwise hybrid Artificial Bee Colony (PhABC), Genetic and Particle Swarm Optimization (GAPSO) algorithm, Hybrid Optimization Algorithm (HOA), and Parameter Free Choice Function based Hyper-Heuristic (PCFHH), among others. …”
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Leaf lesion classification (LLC) algorithm based on artificial bee colony (ABC)
Published 2015“…Results showed that the Leaf Lesion Classification (LLC) algorithm based on Artificial Bee colony (ABC) produced an average 96.83% of accuracy and average 1.66 milliseconds of processing time, indicating that LLC algorithm is better than algorithm such as Otsu, Canny, Roberts and Sobel. …”
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Pairwise Test Suite Generation Based on Hybrid Artificial Bee Colony Algorithm
Published 2020“…Complementing to the earlier researches, this paper proposes a new pairwise test suite generation called Pairwise Hybrid Artificial Bee Colony (PhABC) strategy based on hybridize of an Artificial Bee Colony (ABC) algorithm with a Particle Swarm Optimization (PSO) algorithm. …”
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Sequence-based interaction testing implementation using Bees Algorithm
Published 2023“…In this paper we present a sequence-based interaction testing strategy (termed as sequence covering array) using Bees Algorithm. …”
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Optimisation of support vector machine hyperparameters using enhanced artificial bee colony variant to diagnose breast cancer
Published 2023“…This algorithm named JAABC5ROC is the enhancement of Artificial Bee Colony (ABC) variant, JA-ABC5 by combining with Rate of Change (ROC)\. …”
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Evaluating Bees Algorithm for Sequence-based T-way Testing Test Data Generation
Published 2018“…However, very few strategies have been proposed for sequence-based t-way. This paper presents statistical analysis on the performance of Bees Algorithm against the other sequence t-way strategies, in order to generate test cases.…”
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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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Design And Implementation Of Human Crowd Density Estimation System With Energy Harvesting In Wireless Sensor Network Platform
Published 2017“…To mitigate the limited sensing capability, a human crowd density estimation (H-CDE) system based on ZigBee and wireless sensor network technology is proposed that increases the crowd detection range to 30 m with only one transmission node required every 37.5 m2. …”
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SVM for network anomaly detection using ACO feature subset
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A framework of test case prioritisation in regression testing using particle swarm-artificial bee colony algorithm
Published 2024“…The developed framework, grounded in fault-based testing theory, comprises three key components: inputs, prioritization factors, and a prioritization algorithm. …”
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Edge Detection Algorithm For Image Processing Of Search And Rescue Robot
Published 2016“…This paper highlights the various edge detection algorithms working method and comparison is made based on the advantages and disadvantages of the algorithms for the identification of an optimum edge detection algorithm. …”
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Final Year Project -
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Optimised content-social based features for fake news detection in social media using text clustering approach
Published 2025“…In general, the process of fake news detection was conducted in two different phases, the topic detection phase using a graph-based unsupervised clustering method based on HFPA and Markov Clustering Algorithm (MCL) called (HFPA-MCL) and the fake news detection phase using an unsupervised clustering method based on K-means algorithm. …”
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Machine learning algorithms in context of intrusion detection
Published 2016“…Asymmetrically, anomaly based detection method can detect novel attacks but it has high false positive rate. …”
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