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  1. 1
    An ensemble learning method for spam email detection system based on metaheuristic algorithms

    An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

    Published 2015
    “…In order to address the challenges that mentioned above in this study, in the first phase, a novel architecture based on ensemble feature selection techniques include Modified Binary Bat Algorithm (NBBA), Binary Quantum Particle Swarm Optimization (QBPSO) Algorithm and Binary Quantum Gravita tional Search Algorithm (QBGSA) is hybridized with the Multi-layer Perceptron (MLP) classifier in order to select relevant feature subsets and improve classification accuracy. …”
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  2. 2
    An improved algorithm for iris classification by using support vector machine and binary random machine learning

    An improved algorithm for iris classification by using support vector machine and binary random machine learning by Kamarulzalis, Ahmad Haadzal

    Published 2018
    “…The first objective of this study is to improve a new algorithm technique for classification. The new algorithm come from a combination of an ideas of k-NN algorithm and ensemble concept. …”
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  3. 3
    Arabic text classification using hybrid feature selection method using chi-square binary artificial bee colony algorithm

    Arabic text classification using hybrid feature selection method using chi-square binary artificial bee colony algorithm by Hijazi, Musab, Zeki, Akram M., Ismail, Amelia Ritahani

    Published 2021
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  4. 4
    Feature and Instances Selection for Nearest Neighbor Classification via Cooperative PSO

    Feature and Instances Selection for Nearest Neighbor Classification via Cooperative PSO by Sharifah Sakinah, Syed Ahmad

    Published 2014
    “…The proposed method is applied to 14 real world dataset from the machine learning repository. The algorithm’s performance is illustrated by the corresponding table of the classification rate. …”
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  5. 5
    Unsupervised logic mining with a binary clonal selection algorithm in multi-unit discrete Hopfield neural networks via weighted systematic 2 satisfiability

    Unsupervised logic mining with a binary clonal selection algorithm in multi-unit discrete Hopfield neural networks via weighted systematic 2 satisfiability by Romli, Nurul Atiqah, Zulkepli, Nur Fariha Syaqina, Kasihmuddin, Mohd Shareduwan Mohd, Zamri, Nur Ezlin, Rusdi, Nur 'Afifah, Manoharam, Gaeithry, Mansor, Mohd. Asyraf, Jamaludin, Siti Zulaikha Mohd, Malik, Amierah Abdul

    Published 2024
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  6. 6
    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
    “…Experiments demonstrate and prove that the proposed EBPSO method produces better accuracy mining data and selecting subset of relevant features comparing other algorithms. …”
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  7. 7
    Logic mining method via hybrid discrete hopfield neural network

    Logic mining method via hybrid discrete hopfield neural network by Guo, Yueling, Mohd Kasihmuddin, Mohd Shareduwan, Zamri, Nur Ezlin, Li, Jia, Romli, Nurul Atiqah, Mansor, Mohd Asyraf, Ruzai, Wan Nur Aqlili

    Published 2025
    “…Despite the success, the limitations of existing logic mining methods are often overlooked, hindering the search for optimal solutions in binary classification tasks. …”
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  8. 8
    Named entity recognition using a new fuzzy support vector machine.

    Named entity recognition using a new fuzzy support vector machine. by Mansouri, Alireza, Affendy, Lilly Suriani, Mamat, Ali

    Published 2008
    “…The design of our method is a kind of One-Against-All multi classification technique to solve the traditional binary classifier in SVM.…”
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  9. 9
    Class binarization with self-adaptive algorithm to improve human activity recognition

    Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

    Published 2018
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  10. 10
    Schelkunoff array synthesis methods using adaptive-iterative algorithm

    Schelkunoff array synthesis methods using adaptive-iterative algorithm by Abdul Latiff, Nurul Mu'azzah

    Published 2003
    “…Basically, this algorithm is a combination of iterative algorithm with adaptive algorithm. …”
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  11. 11
    Enhancement of new smooth support vector machines for classification problems

    Enhancement of new smooth support vector machines for classification problems by Santi Wulan, Purnami

    Published 2011
    “…Research on Smooth Support Vector Machine (SSVM) for classification problem is an active field in data mining. …”
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  12. 12
    An Integrated Approach to the Reduction of Reactive Power Losses in Radial Distribution Network

    An Integrated Approach to the Reduction of Reactive Power Losses in Radial Distribution Network by Than, Khong Hon

    Published 2004
    “…The objective of this project is to compensate reactive power with appropriate methods. There are basically two commonly usedmethods: network reconfiguration and capacitor insertion. …”
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  13. 13
    Overview of biomedical relations extraction using hybrid rule-based approaches.

    Overview of biomedical relations extraction using hybrid rule-based approaches. by Abdul Kadir, Rabiah, Bokharaeian, Behrouz

    Published 2013
    “…These huge amounts of information cause very difficult task of extraction or classification.Therefore, there is a need for knowledge discovery and text mining tools in this field. …”
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  14. 14
    Multitasking deep neural network models for Arabic dialect sentiment analysis

    Multitasking deep neural network models for Arabic dialect sentiment analysis by Alali, Muath Mohammad Oqlah

    Published 2022
    “…Therefore, a model called Multi-Tasking Learning based on Convolutional Hierarchical Attention Neural Network (MTL-CHAN) is proposed, comprising of (i) shared word encoder and word attention networks across classification tasks, (ii) task-specific layers with convolutional neural network-based attention (CNNA) on sentence-level; to handle the Arabic explicit negation words and improve the classification performance by training Arabic classification tasks (binary, ternary, and five) jointly. …”
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  15. 15
    Hybrid Neural Network With K-Means For Forecasting Response Candidate In Direct Marketing

    Hybrid Neural Network With K-Means For Forecasting Response Candidate In Direct Marketing by Ramadhan, Rakhmat Sani

    Published 2014
    “…This research concerns on binary classification which is classified into two classes. …”
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  16. 16
    Development of a new nonlinear filtering algorithm for impulse noise reduction

    Development of a new nonlinear filtering algorithm for impulse noise reduction by Ahmad, Mohd Ashraf

    Published 2020
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  17. 17
    Finger vein verification system using repeated line tracking and dimensionality reduction using PCA algorithms with SURF matching

    Finger vein verification system using repeated line tracking and dimensionality reduction using PCA algorithms with SURF matching by Ei Wei., Ting, M. Z., Ibrahim, D.J., Mulvaney

    Published 2017
    “…The feature vector of the vein pattern was then dimensionality reduction by Principal Component Analysis (PCA). The Speeded-Up Robust Features (SURF) Algorithms is used to determine the interest points. …”
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  18. 18
    Effect of model simplification through manual reduction in number of surfaces on room acoustics simulation

    Effect of model simplification through manual reduction in number of surfaces on room acoustics simulation by Abd Jalil, Nurul Amira, Che Din, Nazli, Keumala, Nila, Abdul-Razak, Asrul Sani

    Published 2019
    “…Various simplification algorithms were previously suggested. However, they are highly demanding methods, which are more suitable for large complicated spaces. …”
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  19. 19
    Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman

    Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman by Che Osman, Siti Eshah

    Published 2019
    “…The final results have proved that HPSO algorithm could achieve 5% - 34% of computation cost reduction with satisfying degradation value of image quality. …”
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  20. 20
    Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.

    Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining. by Saeed, Walid

    Published 2005
    “…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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