Search Results - (( subset detection model algorithm ) OR ( based optimization _ algorithm ))*
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1
Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi
Published 2019“…In fact a data clustering method is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on our proposed algorithm; which is Enhanced Binary Particle swarm Optimization (EBPSO), (ii) To mine data using various data chunks (windows) and overcome a failure of single clustering. …”
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2
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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3
SVM for network anomaly detection using ACO feature subset
Published 2016“…But irrelevant and redundant features are the obstacle for classification algorithm to build an efficient detection model. This paper proposes a detection model, ant system with support vector machine, which uses ant system, a variation of ant colony optimization, to filter out the redundant and irrelevant features for support vector machine classification algorithm. …”
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4
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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5
Heart disease prediction using artificial neural network with ADAM optimization and harmony search algorithm
Published 2025“…Drawing from an extensive review of existing predictive models and cardiovascular health risk factors, this research proposes an enhanced ADAM optimization algorithm, integrated with advanced data processing and feature selection methodologies, to identify and refine key predictors for improved model performance. …”
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6
Hyperparameter tuned deep learning enabled intrusion detection on internet of everything environment
Published 2022“…In addition, Chaotic Local Search Whale Optimization Algorithm-based Feature Selection (CLSWOA-FS) technique is employed to choose the optimal feature subsets. …”
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7
Sleep arousal events detection using PNN-GBMO classifier based on EEG and ECG signals: A hybrid-learning model
Published 2020“…The notion is very effective in the detection of sleep disorders. In this paper, the detection of arousal events is performed using an automatic analysis of EEG and ECG signals. …”
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8
Qualitative and quantitative accuracy evaluation of 18f-fdg PET/CT with TOF and NON-TOF system on beta value in BPL reconstruction
Published 2024“…Methods: A National Electrical Manufacturers Association (NEMA) image quality phantom filled with Fluorine-18 fluoro-2-deoxy-D-glucose (18F-FDG) at a 5:1 tumour-to-background ratio (TBR) was scanned on a lutetium-based PET/CT scanner. The images were reconstructed using the OSEM (16 subsets, 3 iterations) and Q.Clear algorithms, both of which include Point Spread Function (PSF) modelling. …”
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9
Automated underwater vision system for detection and classification of marine life using CNN YOLO-based model / Mohamed Syazwan Asyraf Rosli
Published 2022“…Hence, the proposed YOLO model is further improved based on the model optimization using a challenging The Brackish Dataset. …”
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10
MRFGRO: a hybrid meta-heuristic feature selection method for screening COVID-19 using deep features
Published 2021“…Then, we have proposed a hybrid meta-heuristic feature selection (FS) algorithm, named as Manta Ray Foraging based Golden Ratio Optimizer (MRFGRO) to select the most significant feature subset. …”
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11
Robust techniques for linear regression with multicollinearity and outliers
Published 2016“…The ordinary least squares (OLS) method is the most commonly used method in multiple linear regression model due to its optimal properties and ease of computation. …”
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12
Development of a hybrid machine learning model for rockfall source and hazard assessment using laser scanning data and GIS
Published 2019“…This is based on an integration of Gaussian Mixture Model (GMM) and an ensemble Artificial Neural Network (Bagged ANN -BANN) for automatic detection of potential rockfall sources at Kinta Valley area, Malaysia. …”
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13
Intrusion Detection in Mobile Ad Hoc Networks Using Transductive Machine Learning Techniques
Published 2011“…Feature selection is undertaken to select the relevant subsets of features to build an efficient prediction model and improve intrusion detection performance by removing irrelevant features. …”
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Optimization of feature selection in Support Vector Machines (SVM) using recursive feature elimination (RFE) and particle swarm optimization (PSO) for heart disease detection
Published 2024“…One effective approach to detect heart disease is to use Support Vector Machine (SVM) as a machine learning algorithm. …”
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Proceeding Paper -
16
Adaptive feature selection for denial of services (DoS) attack
Published 2017“…Adaptive detection is the learning ability to detect any changes in patterns in intrusion detection systems. …”
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17
Modelling and analysis of sensor fault tolerant control using behavioral approach to systems theory
Published 2015“…Mathematical models of the plants are first derived through the description of the manifest behavior by elimination of the latent variables via a systematic algorithm. …”
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18
Classification of Immunosignature Using Random Forests for Cancer Diagnosis
Published 2015“…We have used the Random Subset gene selection method to avoid overfitting and improve model performance in order to make the input data suitable for the classification stage, which has been implemented using the Random Forest (RF) classifier. …”
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Proceeding Paper -
19
Deep learning-based breast cancer detection and classification using histopathology images / Ghulam Murtaza
Published 2021“…Several studies developed BrC detection and classification models using Hp images. …”
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20
Dual-layer ranking feature selection method based on statistical formula for driver fatigue detection of EMG signals
Published 2022“…This work proposed a dual-layer ranking feature selection algorithm based on statistical formula f EMG signals for driver fatigue detection. …”
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