Search Results - (( data optimization method algorithm ) OR ( using detection technique algorithm ))
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1
An improved method using fuzzy system based on hybrid boahs for phishing attack detection
Published 2022“…Moreover, Butterfly Optimization Algorithm and Harmony Search Algorithm were combined as optimization method led to a new method named BOAHS. …”
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2
Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi
Published 2019“…An efficient IDS uses computational methods as techniques of machine learning (ML) to enhance the rates of detection to obtain the lowest false positive rate, although such rates tend to be reduced by the big amount of irrelevant features as an optimization issue. …”
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3
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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4
An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…Recently, various techniques based on different algorithms have been developed. …”
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5
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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6
Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm
Published 2023“…It provides an increased convergence and globally optimized solutions. The algorithm has been tested using actual customer consumption data from SESB. 10 fold cross validation method is used to confirm the consistency of the detection accuracy. …”
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Optimized techniques for landslide detection and characteristics using LiDAR data
Published 2018“…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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8
An efficient IDS using hybrid Magnetic swarm optimization in WANETs
Published 2018“…In order to improve the effectiveness of intrusion detection systems (IDSs), data analysis methods such as data mining and classification methods are often integrated with IDSs. …”
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Classification Algorithms and Feature Selection Techniques for a Hybrid Diabetes Detection System
Published 2021“…Several combinations of Harmony search algorithm, genetic algorithm, and particle swarm optimization algorithm are examined with K-means for feature selection. …”
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10
Failure detection analysis of grid-connected photovoltaic systems in tropical climate region / Nurmalessa Muhammad @ Atan
Published 2020“…A modified threshold-based technique was used to build the FD algorithm based on data from PV system installed at GERC UiTM, Malaysia. …”
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11
An Efficient IDS Using Hybrid Magnetic Swarm Optimization in WANETs
Published 2018“…In order to improve the effectiveness of intrusion detection systems (IDSs), data analysis methods such as data mining and classification methods are often integrated with IDSs. …”
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Pre-processing methods for vehicle lane detection / Muhammad Naim Mazani ... [et al.]
Published 2020“…This study presents pre-processing methods for detecting lane detection using camera and Light Detection and Ranging (LiDAR) sensor technologies. …”
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13
Representation Of Rational Bézier Quadratics Using Genetic Algorithm, Differential Evolution And Particle Swarm Optimization
Published 2013“…These techniques have been used to optimize control points and weights in the description of spline functions used. …”
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14
Test case generation from state machine with OCL constraints using search-based techniques / Aneesa Ali Ali Saeed
Published 2017“…In order to generate optimal data to satisfy whole constraints in the feasible path, new method with SBTs is necessary to satisfy the whole constraints at the same time of the whole path executing. …”
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15
A hybrid deep learning-based unsupervised anomaly detection in high dimensional data
Published 2022“…The first is the dataset class imbalance, which solved using SMOTE technique. The second issue is the poor performance, which can be solved using one of the optimization algorithms. …”
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16
Traditional marble game using ant colony optimization / Muhammad Izzat Imran Che Isa
Published 2017“…The study of traditional marble game will be implemented in a game prototype using Ant Colony Optimization (ACO). ACO technique is used for searching method in order to find the nearest marble that can be selected to be shot. …”
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17
Backpropagation neural network based on local search strategy and enhanced multi-objective evolutionary algorithm for breast cancer diagnosis
Published 2019“…However, the performance of such methods is based on the algorithms or technique. In this paper, we develop an intelligent technique using multiobjective evolutionary method hybrid with a local search approach to enhance the backpropagation neural network. …”
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18
Early detection of dengue disease using extreme learning machine
Published 2018“…The availability of nowadays clinical data of Dengue disease can be used to train machine learning algorithm in order to automaticaly detect the present of Dengue disease of the patients. …”
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Optimizing the light gradient-boosting machine algorithm for an efficient early detection of coronary heart disease
Published 2024“…This aimed to optimize the Light Gradient-Boosting Machine (LightGBM) algorithm to enhance its performance and accuracy in the early detection of CHD, providing a reliable, cost-effective, and non-invasive diagnostic tool. …”
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20
Development of optimized damage prediction method for health monitoring of ultra high performance fiber-reinforced concrete communication tower
Published 2018“…Therefore, this study aims to develop a new health monitoring system for communication towers based on AdaBoost, Bagging, and RUSBoost algorithms as hybrid algorithm, which can predict the damage by using noisy, random, unstable, and skewed frequency data with high accuracy. …”
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