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  1. 1
    Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm

    Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm by Shahrizal, Saat, Mohd Ashraf, Ahmad, Mohd Riduwan, Ghazali

    Published 2025
    “…The MSEDA was used to tune the brain emotional learning-based intelligent controller (BELBIC) together with a proportional-integral-derivative (PID) controller. …”
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  2. 2
    Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm

    Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm by Shahrizal, Saat, Mohd Ashraf, Ahmad, Mohd Riduwan, Ghazali

    Published 2025
    “…The MSEDA was used to tune the brain emotional learning-based intelligent controller (BELBIC) together with a proportional-integral-derivative (PID) controller. …”
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  3. 3
    Clustering natural language morphemes from EEG signals using the Artificial Bee Colony algorithm

    Clustering natural language morphemes from EEG signals using the Artificial Bee Colony algorithm by Sulaiman, Suriani, Ahmed Yahya, Saba, Mohd Shukor, Nur Sakinah, Ismail , Amelia Ritahani, Zaahirah, Qazi, Yaacob, Hamwira Sakti, Abdul Rahman, Abdul Wahab, Dzulkifli, Mariam Adawiah

    Published 2015
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  4. 4
    The development of extra axial brain tumor detection prototype using back propagation based neural network / Suriyanti Panagen

    The development of extra axial brain tumor detection prototype using back propagation based neural network / Suriyanti Panagen by Panagen, Suriyanti

    Published 2006
    “…This project is about detecting which type of extra axial brain tumor suffered by patient using the artificial intelligence approach. Artificial intelligence method that used in this system is artificial neural network. …”
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  5. 5
    Nature-Inspired cognitive evolution to play Ms. Pac-Man

    Nature-Inspired cognitive evolution to play Ms. Pac-Man by Tse, Guan Tan, Jason Teo, Patricia Anthony

    Published 2011
    “…In essence, a neural network is an attempt to mimic the extremely complex human brain system, which is building an artificial brain that is able to self-learn intelligently. …”
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  6. 6
    Evaluation of intracerebral haemorrhages surface area using artificial intelligence in computed tomography

    Evaluation of intracerebral haemorrhages surface area using artificial intelligence in computed tomography by Huddin, Azzam Basseri, Huddin, Aqilah Baseri, Tharek, Anas, Wan Zaki, Wan Mimi Diyana, Muda, Ahmad Sobri

    Published 2022
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  7. 7
    Detection of partial seizure: An application of fuzzy rule system for wearable ambulatory systems

    Detection of partial seizure: An application of fuzzy rule system for wearable ambulatory systems by Shakir, Mohamed, Malik, Aamir Saeed, Kamel , Nidal, Qidwai, Uvais

    Published 2014
    “…Electroencephalography (EEG) plays an intelligent role, especially EEG based health diagnosis of brain disorder, as well as brain-computer interface (BCI) applications. …”
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  8. 8
    Neural network in handwritten recognition system: A survey

    Neural network in handwritten recognition system: A survey by Wan Ishak, Wan Hussain, Abdul Rahman, Shuzlina

    Published 2003
    “…Neural network is a branch of Artificial Intelligence that imitates the biological processing function of the brain. …”
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  9. 9
    Development of a steady state visual evoked potential (SSVEP)-based brain computer interface (BCI) system

    Development of a steady state visual evoked potential (SSVEP)-based brain computer interface (BCI) system by Leow, R.S., Ibrahim, F., Moghavvemi, M.

    Published 2007
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  10. 10
    Development of Straight Line Robot Movement Using Digital Compas Module

    Development of Straight Line Robot Movement Using Digital Compas Module by Wan Ismail, Ibrahim, Mohd Riduwan, Ghazali, Mohd Zaidi, Mohd Tumari

    Published 2012
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  11. 11
    Detection of partial seizure: An application of fuzzy rule system for wearable ambulatory systems

    Detection of partial seizure: An application of fuzzy rule system for wearable ambulatory systems by Shakir, M., Malik, A.S., Kamel, N., Qidwai, U.

    Published 2014
    “…Electroencephalography (EEG) plays an intelligent role, especially EEG based health diagnosis of brain disorder, as well as brain-computer interface (BCI) applications. …”
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  12. 12
    Brain lesion image segmentation using modified U-NET architecture

    Brain lesion image segmentation using modified U-NET architecture by Lee, Xin Yin, Mohd Jamil, Mohamed Mokhtarudin, Ramli, Junid

    Published 2024
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  13. 13
    Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool

    Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool by Nurshafiqa Saffah, Mohd Sharif

    Published 2018
    “…The use of sensors known as Brain-Computer Interface (BCI) tool can monitor the physical processes and mental states that occur in the human brain. …”
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  14. 14
    Optimization of least squares support vector machine technique using genetic algorithm for electroencephalogram multi-dimensional signals

    Optimization of least squares support vector machine technique using genetic algorithm for electroencephalogram multi-dimensional signals by Ahmad, Farzana Kabir, Al-Qammaz, Abdullah Yousef Awwad, Yusof, Yuhanis

    Published 2016
    “…Human-computer intelligent interaction (HCII) is a rising field of science that aims to refine and enhance the interaction between computer and human. …”
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  15. 15
    Brain tumor MRI medical images classification with data augmentation by transfer learning of VGG16

    Brain tumor MRI medical images classification with data augmentation by transfer learning of VGG16 by Ahmed Yahya Al-Galal, Sabaa, Taha Alshaikhli, Imad Fakhri, Abdulrazzaq, M. M., Hassan, Raini

    Published 2021
    “…The ability to estimate conclusions without direct human input in healthcare systems via computer algorithms is known as Artificial intelligence (AI) in healthcare. …”
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  16. 16
    Brain machine interface: classification of mental tasks using short-time PCA and recurrent neural networks

    Brain machine interface: classification of mental tasks using short-time PCA and recurrent neural networks by Hema, Chengalvarayan Radhakrishnamurthy, Paulraj, Murugesapandian, Sazali, Yaacob, Abd Hamid, Adom, Ramachandran, Nagarajan

    Published 2009
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  17. 17
    Neuro Symbolic Integration and Agent Based Modelling

    Neuro Symbolic Integration and Agent Based Modelling by Sathasivam , Saratha, Velavan, Muraly

    Published 2018
    “…Meanwhile, neural networks, known as a mathematical model of neurons in the human brain, and have various abilities, and moreover, they also provide parallel computations and therefore can perform some calculations quicker than classical learning algorithms. …”
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  18. 18
    Current applications of machine learning in dentistry

    Current applications of machine learning in dentistry by Ghazali, Ahmad Badruddin, Reduwan, Nor Hidayah, Ibrahim, Roliana

    Published 2022
    “…Artificial intelligence (AI) is the general description given to computer systems that can perform tasks and mimic the requirement of human intelligence input (Pesapane et al., 2018). …”
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  19. 19
    Multi-method diagnosis of CT images for rapid detection of intracranial hemorrhages based on deep and hybrid learning

    Multi-method diagnosis of CT images for rapid detection of intracranial hemorrhages based on deep and hybrid learning by Mohammed, Badiea Abdulkarem, Senan, Ebrahim Mohammed, Al-Mekhlafi, Zeyad Ghaleb, Rassem, Taha Hussein, Makbol, Nasrin M., Alanazi, Adwan Alownie, Almurayziq, Tariq S., Ghaleb, Fuad A., Sallam, Amer A.

    Published 2022
    “…The third proposed system uses artificial neural networks (ANNs) based on the features of the GoogLeNet, ResNet-50 and AlexNet models, whose dimensions are reduced by a principal component analysis (PCA) algorithm, and then the low-dimensional features are combined with the features of the GLCM and LBP algorithms. …”
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  20. 20
    Obso based fractional pid for mppt-pitch control of wind turbine systems

    Obso based fractional pid for mppt-pitch control of wind turbine systems by Mehedi, I.M., Al-Saggaf, U.M., Vellingiri, M.T., Milyani, A.H., Saad, N.B., Yahaya, N.Z.B.

    Published 2022
    “…Besides, the pitch controller needs to be intelligent for the extraction of sustainable secure energy and keep WTs in a safe operating region. …”
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