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  1. 1
    An improved pheromone-based kohonen self-organising map in clustering and visualising balanced and imbalanced datasets

    An improved pheromone-based kohonen self-organising map in clustering and visualising balanced and imbalanced datasets by Azlin, Ahmad, Rubiyah, Yusof, Nor Saradatul Akmar, Zulkifli, Mohd Najib, Ismail

    Published 2021
    “…However, similar to other clustering algorithms, this algorithm requires sufficient data for its unsupervised learning process. …”
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  2. 2
    Optimisation of fed-batch fermentation process using deep reinforcement learning

    Optimisation of fed-batch fermentation process using deep reinforcement learning by Chai, Wan Ying

    Published 2023
    “…Deep reinforcement learning is a self-learning algorithm through trial and error and experience, without any prior knowledge. …”
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  3. 3
    An Improved Pheromone-Based Kohonen Self- Organising Map in Clustering and Visualising Balanced and Imbalanced Datasets

    An Improved Pheromone-Based Kohonen Self- Organising Map in Clustering and Visualising Balanced and Imbalanced Datasets by Ahmad, Azlin, Yusof, Rubiyah, Zulkifli, Nor Saradatul Akma, Ismail, Mohd Najib

    Published 2021
    “…However, similar to other clustering algorithms, this algorithm requires sufficient data for its unsupervised learning process. …”
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  4. 4
    An improved self organizing map using jaccard new measure for textual bugs data clustering

    An improved self organizing map using jaccard new measure for textual bugs data clustering by Ahmed, Attika

    Published 2018
    “…Considering the unsupervised learning algorithms, Self-Organizing Map (SOM) considers the equally compatible algorithm for clustering, as both algorithms are closely related but different in way they were used in data mining. …”
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  5. 5
    An improved self organizing map using jaccard new measure for textual bugs data clustering

    An improved self organizing map using jaccard new measure for textual bugs data clustering by Ahmed, Attika

    Published 2018
    “…Considering the unsupervised learning algorithms, Self­Organizing Map (SOM) considers the equally compatible algorithm for clustering, as both algorithms are closely related but different in way they were used in data mining. …”
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  6. 6
    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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  7. 7
    Quantum-Inspired Multidirectional Associative Memory With a Self-Convergent Iterative Learning

    Quantum-Inspired Multidirectional Associative Memory With a Self-Convergent Iterative Learning by Masuyama, Naoki, Loo, Chu Kiong, Seera, Manjeevan, Kubota, Naoyuki

    Published 2018
    “…The self-convergent iterative learning enables the network to progressively develop a resonance state, from inputs to outputs. …”
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  8. 8
    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
    “…In the learning process the network first forms mapping from each motor representation onto visual representation from the self-exploratory perspective. …”
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  9. 9
    The implications for ahybrid detection technique against malicious sqlattacks on web applications

    The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

    Published 2025
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  10. 10
    Self-organizing network technique for resource allocation and mobility management in LTE femtocell network / Labeeb Mohsin Abdullah

    Self-organizing network technique for resource allocation and mobility management in LTE femtocell network / Labeeb Mohsin Abdullah by Abdullah, Labeeb Mohsin

    Published 2015
    “…In this thesis, the issues of concern include assigning the limited resources of Physical Cell Identity (PCI) for the high number of deployed femtocells, to ensure network collision and confusion free after deploying the PCI, determine the exact geographic location of femtocell, and identifying the learning parameters for the optimized self—organizing handover process for LTE femtocell-based networks. …”
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  11. 11
    Academic leadership bio-inspired classification model using negative selection algorithm

    Academic leadership bio-inspired classification model using negative selection algorithm by Jantan, Hamidah, Sa’dan, Siti ‘Aisyah, Che Azemi, Nur Hamizah Syafiqah

    Published 2015
    “…Negative selection algorithm has been successfully used in several purposes such as in fault detection, data integrity protection, virus detection and etc.due to the unique ability in self-recognition by classifying self or non-self’s detectors. …”
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  12. 12
    A Survey of Stochastic processes in Wireless Sensor Network: a Power Management Prospective

    A Survey of Stochastic processes in Wireless Sensor Network: a Power Management Prospective by Ul haq, Riaz, Norrozila, Sulaiman, Muhammad, Alam

    Published 2013
    “…This survey is focusing on the stochastic process based power management algorithms for the WSN field. …”
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  13. 13
    Localization for autonomous car using deep learning

    Localization for autonomous car using deep learning by Lee, Woon Shin

    Published 2023
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  14. 14
    The development of a tracking algorithm for ambulance detection using squaring of RGB and HSV color processing techniques

    The development of a tracking algorithm for ambulance detection using squaring of RGB and HSV color processing techniques by Mohammad Syawaludin Syafiq, Hassan

    Published 2016
    “…In this study, a tracking algorithm is developed by means of image processing technique in detecting ambulance. …”
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  15. 15
    Intelligent agent for e-commerce using genetic algorithm / Kok Sun Sun

    Intelligent agent for e-commerce using genetic algorithm / Kok Sun Sun by Kok , Sun Sun

    Published 2000
    “…In order to develop an intelligent agent, various programming techniques are used in achieving the property of self learning, information retrieval and searching algorithm. …”
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  16. 16
    Intent-IQ: customer’s reviews intent recognition using random forest algorithm

    Intent-IQ: customer’s reviews intent recognition using random forest algorithm by Mazlan, Nur Farahnisrin, Ibrahim Teo, Noor Hasimah

    Published 2025
    “…Two machine learning model is chosen to build the classification models which are Random Forest (RF) algorithm and Multinomial Naïve Bayes (MNB) algorithm. …”
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  17. 17
    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
    “…AIS has the abilities of self-organizing, memory, recognition, adaptive and ability of learning inspired from the immune system. …”
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  18. 18
    Fake news detection: A machine learning approach

    Fake news detection: A machine learning approach by Yeoh, Dennis Guan Lee

    Published 2021
    “…Once the dataset was created, several machine learning algorithms were used to train several different models. …”
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  19. 19
    Self learning module on securing IPV6 deployment / Muhamad Nazif Shahaimi Zaha

    Self learning module on securing IPV6 deployment / Muhamad Nazif Shahaimi Zaha by Zaha, Muhamad Nazif Shahaimi

    Published 2019
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  20. 20
    The effect of pre-processing techniques and optimal parameters on BPNN for data classification

    The effect of pre-processing techniques and optimal parameters on BPNN for data classification by HUSSEIN, AMEER SALEH

    Published 2015
    “…The architecture of artificial neural network (ANN) laid the foundation as a powerful technique in handling problems such as pattern recognition and data analysis. It’s data-driven, self-adaptive, and non-linear capabilities channel it for use in processing at high speed and ability to learn the solution to a problem from a set of examples. …”
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