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  1. 1
    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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  2. 2
    A new machine learning-based hybrid intrusion detection system and intelligent routing algorithm for MPLS network

    A new machine learning-based hybrid intrusion detection system and intelligent routing algorithm for MPLS network by Mohammad Azmi Ridwan, Dr.

    Published 2023
    “…The dataset development for both algorithms is carried out via simulations in Graphical Network Simulator 3 (GNS3). …”
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  3. 3
    Hybrid moth flame optimization mppt algorithm for accurate real-time tracking under partially shaded photovoltaic system

    Hybrid moth flame optimization mppt algorithm for accurate real-time tracking under partially shaded photovoltaic system by Tiong, Meng Chung

    Published 2021
    “…To lift the limitation off, a new hybrid model named Hybrid MFO (HMFO) was proposed based on the combination of feature from MFO and conventional P&O, together with an additional partial shading detection feature. …”
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  4. 4
    Wavelet based fault tolerant control of induction motor / Khalaf Salloum Gaeid

    Wavelet based fault tolerant control of induction motor / Khalaf Salloum Gaeid by Gaeid, Khalaf Salloum

    Published 2012
    “…The fault detection algorithm identifies the time and location of each fault. …”
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  5. 5
    Optimised content-social based features for fake news detection in social media using text clustering approach

    Optimised content-social based features for fake news detection in social media using text clustering approach by Yahya, Adnan Hussein Ali

    Published 2025
    “…The accuracy of fake news detection models relies mainly on the quality of the extracted features and the method used in detection. …”
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  6. 6
    Feature selection algorithms for Malaysian dengue outbreak detection model

    Feature selection algorithms for Malaysian dengue outbreak detection model by Husam I.S. Abuhamad, Azuraliza Abu Bakar, Suhaila Zainudin, Mazura Sahani, Zainudin Mohd Ali

    Published 2017
    “…Based on the selected features, three predictive modeling techniques (J48, DTNB and Naive Bayes) were applied for dengue outbreak detection. …”
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  7. 7
    Hybrid weight deep belief network algorithm for anomaly-based intrusion detection system

    Hybrid weight deep belief network algorithm for anomaly-based intrusion detection system by Maseer, Ziadoon Kamil

    Published 2022
    “…In future, the HW-DBN algorithm can be proposed as an integrated deep Learning for the classification performance of attack detection models.…”
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  8. 8
    SVM for network anomaly detection using ACO feature subset

    SVM for network anomaly detection using ACO feature subset by Mehmood, T., Rais, H.B.M.

    Published 2016
    “…But irrelevant and redundant features are the obstacle for classification algorithm to build an efficient detection model. …”
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  9. 9
    Security alert framework using dynamic tweet-based features for phishing detection on twitter

    Security alert framework using dynamic tweet-based features for phishing detection on twitter by Liew, Seow Wooi

    Published 2019
    “…This model is then embedded into the detection algorithm together with the inclusion of dynamic tweet-based features which are not as part of the features used to train a classification model for phishing tweet detection. …”
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  10. 10
    Malware Classification and Detection using Variations of Machine Learning Algorithm Models

    Malware Classification and Detection using Variations of Machine Learning Algorithm Models by Andi Maslan, Andi Maslan, Abdul Hamid, Abdul Hamid

    Published 2025
    “…The purpose of the study is to detect, classify malware attacks using a variety of ML Algorithm models such as SVM, KNN and Neural Network and testing detection performance. …”
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  11. 11
    Automated Face Detection Using Skin Color Segmentation and Viola-Jones Algorithm

    Automated Face Detection Using Skin Color Segmentation and Viola-Jones Algorithm by Ahmad Fakhri, Ab. Nasir, Ahmad Shahrizan, Abdul Ghani, Muhammad Aizzat, Zakaria, Anwar, P. P. Abdul Majeed, Ahmad Najmuddin, Ibrahim

    Published 2019
    “…Other color model such as HSV and benchmarked algorithm are having slightly low detection rates due to some false face detection. …”
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  12. 12
    Intrusion Detection in Mobile Ad Hoc Networks Using Transductive Machine Learning Techniques

    Intrusion Detection in Mobile Ad Hoc Networks Using Transductive Machine Learning Techniques by Farhan, Farhan Abdel-Fattah Ahmad

    Published 2011
    “…The transductive conformal prediction and outlier detection have been employed for feature selection algorithm. …”
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  13. 13
    K-gen phishguard: an ensemble approach for phishing detection with k-means and genetic algorithm

    K-gen phishguard: an ensemble approach for phishing detection with k-means and genetic algorithm by Al-Hafiz, Ali Raheem, Jabir, Adnan J., Subramaniam, Shamala

    Published 2025
    “…This research utilises the web page phishing detection dataset, which consists of 11,430 URLs with 87 features. …”
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  14. 14
    An enhanced binary bat and Markov clustering algorithms to improve event detection for heterogeneous news text documents

    An enhanced binary bat and Markov clustering algorithms to improve event detection for heterogeneous news text documents by Al-Dyani, Wafa Zubair Abdullah

    Published 2022
    “…To address such a problem, this research presents an enhanced ED model that includes improved methods for the crucial phases of the ED model such as Feature Selection (FS), ED, and summarization. …”
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  15. 15
    Extremal region detection and selection with fuzzy encoding for food recognition

    Extremal region detection and selection with fuzzy encoding for food recognition by Razali @ Ghazali, Mohd Norhisham

    Published 2019
    “…Three algorithms were used to accomplish the task of feature representation. …”
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  16. 16
    Machine learning of tax avoidance detection based on hybrid metaheuristics algorithms

    Machine learning of tax avoidance detection based on hybrid metaheuristics algorithms by Masrom, S., Rahman, R.A., Mohamad, M., Rahman, A.S.A., Baharun, N.

    Published 2022
    “…The machine learning models employed automated features selection with hybrid two metaheuristics algorithms namely particle swarm optimization (PSO) and genetic algorithm (GA). …”
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  17. 17
    Machine learning of tax avoidance detection based on hybrid metaheuristics algorithms

    Machine learning of tax avoidance detection based on hybrid metaheuristics algorithms by Masrom, S., Rahman, R.A., Mohamad, M., Rahman, A.S.A., Baharun, N.

    Published 2022
    “…The machine learning models employed automated features selection with hybrid two metaheuristics algorithms namely particle swarm optimization (PSO) and genetic algorithm (GA). …”
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  18. 18
    A YOLO-based deep learning model for Real-Time face mask detection via drone surveillance in public spaces

    A YOLO-based deep learning model for Real-Time face mask detection via drone surveillance in public spaces by A. Mostafa, Salama, Ravi, Sharran, Zebari, Dilovan Asaad, Zebari, Nechirvan Asaad, Mohammed, Mazin Abed, Nedoma, Jan, Martinek, Radek, Deveci, Muhammet, Ding, Weiping

    Published 2024
    “…A data augmentation algorithm is used for feature generation to enhance the model’s training robustness. …”
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  19. 19
    Comparison of malware detection model using supervised machine learning algorithms / Syamir Mohd Shahirudin

    Comparison of malware detection model using supervised machine learning algorithms / Syamir Mohd Shahirudin by Mohd Shahirudin, Syamir

    Published 2022
    “…The objective of this project is to develop the Windows malware detection model using supervised machine learning in Decision Tree, K-NN and Naïve Bayes, to evaluate the performance of malware detection in term of testing and training of the features selection and to compare the accuracy detection model in all three machine learning algorithms. …”
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  20. 20
    Bayesian Network Classifiers for Damage Detection in Engineering Material

    Bayesian Network Classifiers for Damage Detection in Engineering Material by Mohamed Addin, Addin Osman

    Published 2007
    “…The methodology used in the thesis to implement the Bayesian network for the damage detection provides a preliminary analysis used in proposing a novel fea- ture extraction algorithm (f-FFE: the f-folds feature extraction algorithm). …”
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