Search Results - (( self learning algorithm ) OR ( patterns _ algorithm ))

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  1. 1
    BIOLOGICAL INSPIRED INTRUSION PREVENTION AND SELF-HEALING SYSTEM FOR CRITICAL SERVICES NETWORK

    BIOLOGICAL INSPIRED INTRUSION PREVENTION AND SELF-HEALING SYSTEM FOR CRITICAL SERVICES NETWORK by MOHAMED AHMED ELSHEIK, MUNA ELSADIG

    Published 2011
    “…The design features of the proposed system are inspired by the human immune system, integrated with pattern recognition nonlinear classification algorithm and machine learning. …”
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  2. 2
    Characterization of water quality conditions in the Klang River Basin, Malaysia using self organizing map and K-means algorithm

    Characterization of water quality conditions in the Klang River Basin, Malaysia using self organizing map and K-means algorithm by Mohd Sharif, Sharifah, Mohd Kusin, Faradiella, Asha’ari, Zulfa Hanan, Aris, Ahmad Zaharin

    Published 2015
    “…The self organizing map (SOM) combined with the K-means algorithm arranged the data based on the relationships of 25 variables. …”
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  3. 3
    Preserving the topology of self-organizing maps for data analysis: A review

    Preserving the topology of self-organizing maps for data analysis: A review by Bariah, Yusob, Zuriani, Mustaffa, Siti Mariyam, Shamsuddin

    Published 2020
    “…In Kohonen's Self-Organizing Maps (SOM) algorithm, preserving the map structure to represent the real input patterns appears to be a significant process. …”
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  4. 4
    Multilevel learning in Kohonen SOM network for classification problems

    Multilevel learning in Kohonen SOM network for classification problems by Mohd. Yusof, Norfadzila

    Published 2006
    “…Classification is one of the most active research and application areas of neural networks. Self-organizing map (SOM) is a feed-forward neural network approach that uses an unsupervised learning algorithm has shown a particular ability for solving the problem of classification in pattern recognition. …”
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  5. 5
    APPLICATION OF LINK GRAMMAR IN SEMI-SUPERVISED NAMED ENTITY RECOGNITION FOR ACCIDENT DOMAIN

    APPLICATION OF LINK GRAMMAR IN SEMI-SUPERVISED NAMED ENTITY RECOGNITION FOR ACCIDENT DOMAIN by SARI, YUNITA SARI

    Published 2011
    “…For the third contribution, we have applied the Self-Training algorithm which is one of the semi-supervised machines learning technique. …”
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  6. 6
    Immune network algorithm in monthly streamflow prediction at Johor river

    Immune network algorithm in monthly streamflow prediction at Johor river by Mat Ali, Nur Izzah, Abdul Malik, Marlinda, Ismail , Amelia Ritahani

    Published 2014
    “…Immune Network Algorithm is part of the three main algorithm in AIS. …”
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  7. 7
    Survival versus non-survival prediction after acute coronary syndrome in Malaysian population using machine learning technique / Nanyonga Aziida

    Survival versus non-survival prediction after acute coronary syndrome in Malaysian population using machine learning technique / Nanyonga Aziida by Nanyonga , Aziida

    Published 2019
    “…Self-Organizing Feature (SOM) was used to visualize and identify the relationship and pattern between factors affecting mortality after ACS. …”
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  8. 8
    Self learning neuro-fuzzy modeling using hybrid genetic probabilistic approach for engine air/fuel ratio prediction

    Self learning neuro-fuzzy modeling using hybrid genetic probabilistic approach for engine air/fuel ratio prediction by Al-Himyari, Bayadir Abbas

    Published 2017
    “…The model was compared to other learning algorithms for NFS such as Fuzzy c-means (FCM) and grid partition algorithm. …”
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  9. 9
    Immune network algorithm in monthly streamflow prediction at Johor river

    Immune network algorithm in monthly streamflow prediction at Johor river by Mat Ali, Nur Izzah, Abdul Malek, Marlinda, Ismail, Amelia Ritahani

    Published 2015
    “…Immune Network Algorithm is part of the three main algorithm in AIS. …”
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  10. 10
    Analyzing enrolment patterns: modified stacked ensemble statistical learning based approach to educational decision-making

    Analyzing enrolment patterns: modified stacked ensemble statistical learning based approach to educational decision-making by Zun, Liang Chuan, Nursultan Japashov, Soon, Kien Yuan, Tan, Wei Qing, Noriszura Ismail

    Published 2024
    “…Moreover, the introduction of the novel modified stacked ensemble statistical learning-based algorithm had improved predictive accuracy compared to traditional dichotomous logistic regression algorithms on average, particularly at optimal training-to-test ratios of 70:30, 80:20, and 90:10. …”
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  11. 11
    Mobile app of mood prediction based on menstrual cycle using machine learning algorithm / Nur Hazirah Amir

    Mobile app of mood prediction based on menstrual cycle using machine learning algorithm / Nur Hazirah Amir by Amir, Nur Hazirah

    Published 2019
    “…It implemented Supervised Learning algorithm with Bayes’ Theorem model for the calculation of mood prediction using Python programming language. …”
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  12. 12
    Immune network algorithm in monthly streamflow prediction at Johor river

    Immune network algorithm in monthly streamflow prediction at Johor river by Ali N.I.M., Malek M.A., Ismail A.R.

    Published 2023
    “…Immune Network Algorithm is part of the three main algorithm in AIS. …”
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  13. 13
    Analyzing enrolment patterns: Stacked ensemble statistical learning-based approach to educational decision making

    Analyzing enrolment patterns: Stacked ensemble statistical learning-based approach to educational decision making by Chuan, Zun Liang, Chong, Teak Wei, Japashov, Nursultan, Soon, Kien Yuan, Tan, Wei Qing, Noriszura, Ismail, Liong, Choong-Yeun, Tan, Ee Hiae

    Published 2023
    “…Moreover, the introduction of the novel stacked ensemble machine learning algorithm had improved predictive accuracy compared to traditional dichotomous logistic regression algorithms on average, particularly at optimal training-to-test ratios of 70:30, 80:20, and 90:10. …”
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  14. 14
    DeepIoT.IDS: Hybrid deep learning for enhancing IoT network intrusion detection

    DeepIoT.IDS: Hybrid deep learning for enhancing IoT network intrusion detection by A. Mostafa, Salama, Al-Azzawi, Ziadoon Kamil Maseer, Bahaman, Nazrulazhar, Yusof, Robiah, Musa, Omar, Al-rimy, Bander Ali Saleh

    Published 2021
    “…Recently, researchers have suggested deep learning (DL) algorithms to define intrusion features through training empirical data and learning anomaly patterns of attacks. …”
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  15. 15
    An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA

    An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA by Bian, Hui

    Published 2025
    “…However, these algorithms often fall short in consistently detecting and classifying network intrusions, particularly when distinctions between classes are subtle or when facing evolving attack patterns. …”
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  16. 16
    Development of spike train algorithms for physiotherapy assessment using deep learning approaches

    Development of spike train algorithms for physiotherapy assessment using deep learning approaches by Nor Rashid, Fadilla' Atyka

    Published 2021
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  17. 17
    Analyzing enrolment patterns: Modified stacked ensemble statistical learning-based approach to educational decision-making

    Analyzing enrolment patterns: Modified stacked ensemble statistical learning-based approach to educational decision-making by Chuan, Zun Liang, Japashov, Nursultan, Yuan, Soon Kien, Tan, Wei Qing, Noriszura, Ismail

    Published 2024
    “…Moreover, the introduction of the novel modified stacked ensemble statistical learning-based algorithm had improved predictive accuracy compared to traditional dichotomous logistic regression algorithms on average, particularly at optimal training-to-test ratios of 70:30, 80:20, and 90:10. …”
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  18. 18
    Imitation learning through self-exploration : from body-babbling to visuomotor association / Farhan Dawood

    Imitation learning through self-exploration : from body-babbling to visuomotor association / Farhan Dawood by Dawood, Farhan

    Published 2015
    “…The results show that the imitation learning algorithm is able to incrementally learn and associate the observed motion patterns based on the segmentation of motion primitives.…”
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  19. 19
    A lightweight graph-based pattern recognition scheme in mobile ad hoc networks.

    A lightweight graph-based pattern recognition scheme in mobile ad hoc networks. by Raja Mahmood, Raja Azlina, Muhamad Amin, Anang Hudaya, Amir, Amiza, Khan, Asad I.

    Published 2012
    “…The comparison study between DGHN and the iterative, highly computational self organizing map (SOM) is also reviewed. Both algorithms show comparable detection results. …”
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  20. 20
    EEG-based fatigue detection using binary pattern analysis and KNN algorithm

    EEG-based fatigue detection using binary pattern analysis and KNN algorithm by Abd Rahman, Faridah, Roslizan, Iszan Uwais Amer, Gunawan, Teddy Surya, Fitriawan, Helmy, Kartiwi, Mira, Habaebi, Mohamed Hadi

    Published 2024
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