Search Results - (( model detection method algorithm ) OR ( using optimization method algorithm ))
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A hybridization of butterfly optimization algorithm and harmony search for fuzzy modelling in phishing attack detection
Published 2023“…However, it is hard to determine the fuzzy parameter manually in a complex problem, and the process of generating the parameter is called fuzzy modelling. Therefore, an optimization method is needed to solve this issue, and one of the best methods to be applied is Butterfly Optimization Algorithm. …”
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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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Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi
Published 2019“…Thus, this study is looking for better, new dataset and more reliable optimized method for detecting the intrusion with highest accuracy. …”
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Fuzzy modelling using firefly algorithm for phishing detection
Published 2019“…To generate the fuzzy parameters automatically, an optimization method is needed. One of the suitable methods provides the Firefly Algorithm (FA). …”
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Integrating genetic algorithms and fuzzy c-means for anomaly detection
Published 2005“…In this paper we propose an intrusion detection method that combines Fuzzy Clustering and Genetic Algorithms. …”
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Improved Malware detection model with Apriori Association rule and particle swarm optimization
Published 2019“…These rule models are used together with extraction algorithm to classify and detect malicious android application. …”
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Enhanced computational methods for detection and interpretation of heart disease based on ensemble learning and autoencoder framework / Abdallah Osama Hamdan Abdellatif
Published 2024“…However, the challenge of class imbalance and high dimensionality in clinical data significantly impedes the efficacy of Machine Learning (ML) models in this domain. This thesis presents two innovative methods that holistically address these challenges at algorithmic and data levels to enhance heart disease detection. …”
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Optimizing in-car-abandoned children’s sounds detection using deep learning algorithms / Nur Atiqah Izzati Md Fisol
Published 2023“…To address this problem, an optimized in-car-abandoned children's sounds detection model using deep learning algorithms is proposed. …”
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Neural network algorithm-based fall detection modelling
Published 2020“…However, the improvement of model accuracy is still needed. This article presents results of modelling for fall detection system by using nonlinear autoregression neural network NARnet algorithm. …”
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Model of Improved a Kernel Fast Learning Network Based on Intrusion Detection System
Published 2019“…In this paper, the particle swan optimization algorithm (PSO) was used to obtain an optimal set of initial parameters for Reduce Kernel FLN (RK-FLN), thus, creating an optimal RKFLN classifier named PSO-RKELM. …”
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Optimizing the light gradient-boosting machine algorithm for an efficient early detection of coronary heart disease
Published 2024“…Findings The optimized LightGBM model showed significant improvement in early CHD detection. …”
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Optimizing high-density aquaculture rotifer Detection using deep learning algorithm
Published 2022“…In this paper, we present the method and performance to detect rotifer Brachionus plicatilis in 1ml sample automatically using deep learning algorithm YOLOv3. …”
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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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Road damage detection for autonomous driving vehicles using YOLOv8 and salp swarm algorithm
Published 2025“…Consequently, this paper proposes a method to improve the detection accuracy of You Only Look Once version 8 (YOLOv8) using Salp Swarm Algorithm (SSA) for hyperparameter optimization, focusing on eight key parameters. …”
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Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification
Published 2011“…Evolutionary computation (EC) is known to be an effective search and optimization method and in this paper EC is proposed as a model structure selection algorithm. …”
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An ensemble deep learning classifier stacked with fuzzy ARTMAP for malware detection
Published 2023“…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 ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
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Vehicle detection for vision-based intelligent transportation systems using convolutional neural network algorithm
Published 2022“…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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Test case generation from state machine with OCL constraints using search-based techniques / Aneesa Ali Ali Saeed
Published 2017“…The existing infeasible path detection methods are restricted to extended finite state machine (EFSM) models with integer data type only. …”
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