Search Results - (( evolution optimisation based algorithm ) OR ( based detection method algorithm ))
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Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level
Published 2024thesis::doctoral thesis -
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Performance evaluation and benchmarking of an extended computational model of ant colony system for DNA sequence design
Published 2014“…Ant colony system (ACS) algorithm is one of the biologically inspired algorithms that have been introduced to effectively solve a variety of combinatorial optimisation problems. …”
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A competitive co-evolutionary approach for the nurse scheduling problem
Published 2026“…The competitive approach further exhibits smoother convergence behaviour across generations, indicating stronger optimisation dynamics and improved robustness. These findings demonstrate that competitive co-evolution provides an effective and practical alternative to static fitness-based evolutionary methods for nurse scheduling, with broader applicability to healthcare scheduling and constraint optimisation problems.…”
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding
Published 2025“…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding
Published 2025“…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya 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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Stock market turning points rule-based prediction / Lersak Photong … [et al.]
Published 2021“…Finally, rule-based optimisation techniques such as Particle Swarm Optimization (PSO), Differential Evolution (DE) and Grey Wolf Optimizer (GWO) were used to minimise the amount of time employed in the stock market turning points prediction. …”
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Book Section -
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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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Conference or Workshop Item -
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Algorithm enhancement for host-based intrusion detection system using discriminant analysis
Published 2004“…Algorithms for building detection models are usually classified into two categories: misuse detection and anomaly detection. …”
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Thesis -
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Weighting method for modal parameter based damage detection algorithms
Published 2011“…This study proposes weighting method for damage detection algorithms based on the bending mode shapes for beam structures. …”
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Detection of head position using chain code algorithm
Published 2007“…The main contribution of this thesis is it contributes an algorithm of head recognition and detecting which based on image segmentation, Prewitt edge detection and Chain Code algorithm. …”
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Thesis -
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Detection of head position using chain code algorithm
Published 2007“…The main contribution of this thesis is it contributes an algorithm of head recognition and detecting which based on image segmentation, Prewitt edge detection and Chain Code algorithm. …”
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Thesis -
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Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi
Published 2019“…Moreover, shortage of reliable methods on a new dataset for the intrusion detection system and anomaly detection in terms of classification is an issue. …”
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Thesis -
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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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