Search Results - (( parameter detection method algorithm ) OR ( features selection method algorithm ))*
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1
Feature Selection and Classifier Parameter Estimation for Egg Signal Peak Detection using Gravitational Search Algorithm
Published 2014“…The main intention of this study is to find the significant peak features in time domain approach and this can be done using feature selection methods such as gravitational search algorithm (GSA) and particle swarm optimization (PSO). …”
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2
Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System
Published 2020“…Feature selection and classifier parameter tuning are important factors that affect the performance of any intrusion detection system. …”
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3
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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4
Rao-SVM machine learning algorithm for intrusion detection system
Published 2020“…This article presents the development of an improved intrusion detection method for binary classification. In the proposed IDS, Rao Optimization Algorithm, Support Vector Machine (SVM), Extreme Learning Machine (ELM), and Logistic Regression (LR) (feature selection and weighting) were combined with NTLBO algorithm with supervised ML techniques (for feature subset selection (FSS). …”
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5
Extremal region detection and selection with fuzzy encoding for food recognition
Published 2019“…Three algorithms were used to accomplish the task of feature representation. …”
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6
Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems
Published 2022“…The aim of this work is to develop an improved optimization method for IDS that can be efficient and effective in subset feature selection and parameters optimization. …”
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7
Feature extraction and selection algorithm based on self adaptive ant colony system for sky image classification
Published 2023“…The Friedman test result is presented for the performance rank of six benchmark feature selection algorithms and FESSIC algorithm. …”
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8
Taylor-Bird Swarm Optimization-Based Deep Belief Network For Medical Data Classification
Published 2022“…Fuzzy clustering-based filtering methods are introduced for essential feature selection. …”
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9
Identifying and detecting unlawful behavior in video images using genetic algorithm / Shahirah Mohamed Hatim
Published 2016“…GA is used as the method of unlawful behavior detection. Previous research on GA components impact evaluation has identified selection parameter as high potential of increasing GA performance for unlawful behavior detection. …”
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10
Optimized techniques for landslide detection and characteristics using LiDAR data
Published 2018“…The segmentation process was optimized using Fuzzy-based Segmentation Parameter. Also, six techniques: Ant Colony Optimization (ACO), Gain Ratio (GR), Particle Swarm Optimization (PSO) and Genetic Algorithm (GA), Random forest (RF), and Correlation-based Feature Selection (CFS) were used for the feature selection. …”
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11
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“…Apart from that, the choice of C and gamma parameters can affect SVM performance. The RFE method is used to select the most informative and relevant subset of features from a given feature set. …”
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12
Development of hippocampus MRI image segmentation algorithm for progression detection of alzheimer’s disease (AD)
Published 2022“…The active contour method (Chan-Vese) was utilized to extract the ROI parameters (hippocampus). …”
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13
Heart disease prediction using artificial neural network with ADAM optimization and harmony search algorithm
Published 2025“…Complementing this, the Harmony Search Algorithm (HSA) is incorporated to augment data features, facilitating better pattern recognition and enhancing overall classification accuracy through optimized feature engineering. …”
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Improvement on rooftop classification of worldview-3 imagery using object-based image analysis
Published 2019“…Furthermore, a systematic feature selection approach was proposed in which search algorithms (Ant-Search, Best First-Search and Particle Swamp Optimization (PSO) - Search) performance were evaluated to select the most significant features. …”
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15
Hybridization of metaheuristic algorithm in training radial basis function with dynamic decay adjustment for condition monitoring / Chong Hue Yee
Published 2023“…Two metaheuristic algorithms i.e., Harmony Search (HS) and Gravitational Search Algorithm (GSA), are selected to integrate separately with a Radial Basis Function Network with Dynamic Decay Adjustment (RBFN-DDA) to perform condition monitoring in industrial processes. …”
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16
Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level
Published 2024thesis::doctoral thesis -
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Early detection of dengue disease using extreme learning machine
Published 2018“…Therefore, the proposed ELM model can be considered as an alternative algorithm to apply for early detection of Dengue disease.…”
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18
Tracking consistency metric for video surveillance tracking
Published 2009“…These metrics give a measure of the ability of a tracking algorithm to correctly detect or track a target object. …”
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A stacked ensemble deep learning model for water quality prediction / Wong Wen Yee
Published 2023“…The proposed deep learning model renders faster without the use of SMOTE. Any resampling algorithm is not a necessity in the case of this proposed algorithm. …”
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20
Improved Malware detection model with Apriori Association rule and particle swarm optimization
Published 2019“…Particle swarm optimization (PSO) is used to optimize the random generation of candidate detectors and parameters associated with apriori algorithm (AA) for features selection. …”
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