Search Results - (( software detection method algorithm ) OR ( using optimization using algorithm ))
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Improved intrusion detection algorithm based on TLBO and GA algorithms
Published 2021“…Optimization algorithms are widely used for the identification of intrusion. …”
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A hybridization of butterfly optimization algorithm and harmony search for fuzzy modelling in phishing attack detection
Published 2023“…The advantages of both algorithms are used to balance the exploration and exploitation in the searching process. …”
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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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Fuzzy modelling using butterfly optimization algorithm for phishing detection
Published 2020“…To generate the fuzzy parameter automatically, an optimization method is required and Butterfly Optimization Algorithm (BOA) is one of the good methods to be applied. …”
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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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Traditional marble game using ant colony optimization / Muhammad Izzat Imran Che Isa
Published 2017“…In future, traditional marble game can be applied with other search algorithm to optimize the solution…”
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Detecting problematic vibration on unmanned aerial vehicles via genetic-algorithm methods
Published 2024“…The fitness function with the Genetic Algorithm (GA) optimization method is tested and evaluated based on Root Mean Squared Error (RMSE), Mean Absolute Percentage Error (MAPE), and detection time. 51 sets of data have been collected using software in the loop (SITL) methods and are used to determine the effectiveness of the proposed fitness function and GA. …”
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Conference or Workshop Item -
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Fuzzy modelling using firefly algorithm for phishing detection
Published 2019“…FA is a nature-inspired algorithm that uses fireflies’ behavior to interpret data. …”
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Detecting problematic vibration on unmanned aerial vehicles via genetic-algorithm methods
Published 2024“…The fitness function with the Genetic Algorithm (GA) optimization method is tested and evaluated based on Root Mean Squared Error (RMSE), Mean Absolute Percentage Error (MAPE), and detection time. 51 sets of data have been collected using software in the loop (SITL) methods and are used to determine the effectiveness of the proposed fitness function and GA. …”
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Proceeding Paper -
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Vehicle detection for vision-based intelligent transportation systems using convolutional neural network algorithm
Published 2022“…Hardware-based solutions such as radars and LIDAR are been proposed but are too expensive to be maintained and produce little valuable information to human operators at traffic monitoring systems. Software based solutions using traditional algorithms such as Histogram of Gradients (HOG) and Gaussian Mixed Model (GMM) are computationally slow and not suitable for real-time traffic detection. )erefore, the paper will review and evaluate different vehicle detection methods. …”
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Hybrid Artificial Bee Colony Algorithm for t-Way Interaction Test Suite Generation
Published 2019“…The very large number of test cases and time consumption for a test, it is becoming hard to perform exhaustive testing for any software fault detection. For this reason, combinatorial testing (CT) also known as t-way testing, is one of the well-known methods that are used for fault detections to many software systems. …”
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An ensemble deep learning classifier stacked with fuzzy ARTMAP for malware detection
Published 2023“…The emergence of Deep Learning (DL) models allow more training possibilities and improvement in performance. DL models often use gradient descent optimization, i.e., the Back-Propagation (BP) algorithm; therefore, their training and optimization procedures suffer from local sub-optimal solutions. …”
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Automatic Textile Stain Detection Using Yolo Algorithm
Published 2024“…This research paper proposes a novel approach for automatic textile stain detection using the YOLO (You Only Look Once) algorithm, a state-of-the-art object detection model. …”
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An efficient IDS using hybrid Magnetic swarm optimization in WANETs
Published 2018“…Experimental results show that using our proposed IDS based on hybrid MOA-PSO technique provides more accuracy level compared to the use of ANN based on MOA, PSO and genetic algorithm. …”
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Test case generation from state machine with OCL constraints using search-based techniques / Aneesa Ali Ali Saeed
Published 2017“…The results show that the proposed infeasible path detection method was efficient and detect 99 percent of the infeasible paths in the three industrial systems. …”
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Optimized differential evolution algorithm for linear frequency modulation radar signal denoising
Published 2013“…The standard DE algorithm is known as a fixed length optimizer, while our problem demands the need for methods that aren’t tolerated to a fixed individual size, and that was made by altering the mutation and crossover strategies as well as the selection operation. …”
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Optimized intrusion detection mechanism using soft computing techniques
Published 2011“…The selecting of an appropriate number of principal components is a critical problem. So, Genetic Algorithm (GA) is used in the optimum selection of principal components instead of using traditional method. …”
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The effect of replacement strategies of genetic algorithm in regression test case prioritization of selected test cases
Published 2015“…This study presents an optimized regression test case prioritization of selected test cases for object-oriented software using Genetic algorithm with different replacement strategies. …”
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A fast learning network with improved particle swarm optimization for intrusion detection system
Published 2019“…The focus of this research is on the development of a model that can optimize the initial parameters of FLN based on MRPSO to obtain an optimal set of initial parameters for FLN, thus, creating an optimal FLN classifier named as MRPSO-FLN which can improve the efficacy of network intrusion on data sets that contain instances of multiple classes of attacks. …”
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