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  1. 1
    Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi

    Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi by Atefi, Kayvan

    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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  2. 2
    Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems

    Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems by Mohammad Khamees Khaleel, Alsajri

    Published 2022
    “…Most of the currently existing intrusion detection systems (IDS) use machine learning algorithms to detect network intrusion. …”
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  3. 3
    Features selection for intrusion detection system using hybridize PSO-SVM

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…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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  4. 4
    Improved Malware detection model with Apriori Association rule and particle swarm optimization

    Improved Malware detection model with Apriori Association rule and particle swarm optimization by Adebayo, Olawale Surajudeen, Abdul Aziz, Normaziah

    Published 2019
    “…Using a number of rule detectors, the true positive rate of detecting malicious code is maximized, while the false positive rate of wrongful detection is minimized. …”
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  5. 5
    Static code analysis of permission-based features for android malware classification using apriori algorithm with particle swarm optimization

    Static code analysis of permission-based features for android malware classification using apriori algorithm with particle swarm optimization by Adebayo, Olawale Surajudeen, Abdul Aziz, Normaziah

    Published 2015
    “…Using a number of candidate detectors from an improved Apriori Algorithm with Particle Swarm Optimization, the true positive rate of detecting malicious code is maximized, while the false positive rate of wrongful detection is minimized. …”
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  6. 6
    Integrating genetic algorithms and fuzzy c-means for anomaly detection

    Integrating genetic algorithms and fuzzy c-means for anomaly detection by Chimphlee, Witcha, Abdullah, Abdul Hanan, Sap, Noor Md., Chimphlee, Siriporn, Srinoy, Surat

    Published 2005
    “…Our method is able to detect many different types of intrusions, while maintaining a low false positive rate. …”
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  7. 7
    Android Malware classification using static code analysis and Apriori algorithm improved with particle swarm optimization

    Android Malware classification using static code analysis and Apriori algorithm improved with particle swarm optimization by Adebayo, Olawale Surajudeen, Abdul Aziz, Normaziah

    Published 2014
    “…Using a number of candidate detectors, the true positive rate of detecting malicious code is maximized, while the false positive rate of wrongful detection is minimized. …”
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  8. 8
    GPSO versus GA in facial emotion detection

    GPSO versus GA in facial emotion detection by Bashir, Mohammed Ghandi, Ramachandran, Nagarajan, Prof. Dr., Sazali, Yaacob, Prof. Dr., Hazry, Desa, Assoc. Prof. Dr.

    Published 2012
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  9. 9
    Heart disease prediction using artificial neural network with ADAM optimization and harmony search algorithm

    Heart disease prediction using artificial neural network with ADAM optimization and harmony search algorithm by Alyaa Ghazi Mohammed, Mohd Zakree Ahmad Nazri

    Published 2025
    “…Heart diseases represent a leading global health concern, underscoring the imperative for innovative strategies in early detection and prevention to effectively mitigate risks and avert sudden fatalities. …”
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  10. 10
    Optimized intrusion detection mechanism using soft computing techniques

    Optimized intrusion detection mechanism using soft computing techniques by Ahmad, iftikhar, Azween, Abdullah, Alghamdi, Abdullah, Hussain, Muhammad

    Published 2011
    “…Consequently, this method provides optimal intrusion detection mechanism which is capable to minimize amount of features and maximize the detection rates. …”
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  11. 11
    A fast learning network with improved particle swarm optimization for intrusion detection system

    A fast learning network with improved particle swarm optimization for intrusion detection system by Ali, Mohammed Hasan

    Published 2019
    “…In current days the intrusion detection systems (IDS) have several shortcomings such as high rates of false positive alerts, low detection rates of rare but dangerous attacks, and the need for a constant human intervention and tuning. …”
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  12. 12
    Artificial neural networks and genetic algorithm for transformer winding/insulation faults

    Artificial neural networks and genetic algorithm for transformer winding/insulation faults by K.S.R., Rao, K.N., Nashruladin

    Published 2008
    “…Genetic Algorithm is used to derive the optimal key gas ratios to enhance the accuracy of fault detection. …”
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  13. 13
    Hybrid honey badger algorithm with artificial neural network (HBA-ANN) for website phishing detection

    Hybrid honey badger algorithm with artificial neural network (HBA-ANN) for website phishing detection by Muhammad Arif, Mohamad, Muhammad Aliif, Ahmad, Zuriani, Mustaffa

    Published 2024
    “…HBA as metahueristic algorithm is used to optimize the network training process of ANN to improve their performances. …”
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  14. 14
    Optimizing high-density aquaculture rotifer Detection using deep learning algorithm

    Optimizing high-density aquaculture rotifer Detection using deep learning algorithm by Alixson Polumpung, Kit Guan Lim, Min Keng Tan, Sitti Raehanah Muhamad Shaleh, Renee Ka Yin Chin, Kenneth Teo Tze Kin

    Published 2022
    “…Detected rotifer will be counted for estimating the amount of rotifer for feeding or the density population in a rotifer culture. …”
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  15. 15
    Enhanced computational methods for detection and interpretation of heart disease based on ensemble learning and autoencoder framework / Abdallah Osama Hamdan Abdellatif

    Enhanced computational methods for detection and interpretation of heart disease based on ensemble learning and autoencoder framework / Abdallah Osama Hamdan Abdellatif by Abdalla Osama , Hamdan Abdellatif

    Published 2024
    “…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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  16. 16
    APPLICATION OF ANN AND GA FOR TRANSFORMER WINDING/ INSULATION FAULTS

    APPLICATION OF ANN AND GA FOR TRANSFORMER WINDING/ INSULATION FAULTS by NASHRULADIN, KHAIRUN NISA'

    Published 2007
    “…While, heuristic method of Genetic Algorithm is used to locate the optimal values to enhance the accuracy of fault detection. …”
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  17. 17
    An efficient anomaly intrusion detection method with evolutionary neural network

    An efficient anomaly intrusion detection method with evolutionary neural network by Sarvari, Samira

    Published 2020
    “…The third proposed method is a new Evolutionary Neural Network (ENN) algorithm with a combination of Genetic Algorithm and Multiverse Optimizer (GAMVO) as a training part of ANN to create efficient anomaly-based detection with low false alarm rate. …”
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  18. 18
    Electroencephalogram signal interpretation system for mobile robot

    Electroencephalogram signal interpretation system for mobile robot by Hasan, Intan Helina

    Published 2013
    “…Using sample datasets, the EEG signal is analyzed to determine the most suitable scalp area for P300 detection, while optimization with genetic algorithm (GA) is developed to select best four channels. …”
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  19. 19
    A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem

    A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem by Mohd Pozi, Muhammad Syafiq

    Published 2016
    “…The main keys of the new classifier are based on the new kernel method, new learning metric and a new optimization algorithm in order to optimize the SVM decision function. …”
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  20. 20
    Fair bandwidth distribution marking and scheduling algorithm in network traffic classification

    Fair bandwidth distribution marking and scheduling algorithm in network traffic classification by Al-Kharasani, Ameen Mohammed Abdulkarem

    Published 2019
    “…Finally, propose a new method of obtaining optimal parameters dropping functions for Random Early Detection (RED) algorithm. …”
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