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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
    Detection of eye movements based on EEG signals and the SAX algorithm

    Detection of eye movements based on EEG signals and the SAX algorithm by Shanmuga, P. M. M., Lau, Sian Lun *, Jou, Chichang.

    Published 2018
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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
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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
    Feature Selection and Classifier Parameter Estimation for Egg Signal Peak Detection using Gravitational Search Algorithm

    Feature Selection and Classifier Parameter Estimation for Egg Signal Peak Detection using Gravitational Search Algorithm by Zuwairie, Ibrahim, Mohd Zaidi, Mohd Tumari, Asrul, Adam, Norrima, Mokhtar, Marizan, Mubin, Mohd Ibrahim, Shapiai

    Published 2014
    “…This study focuses on using GSA method, a new computational intelligence algorithm. Moreover, a rule-based classifier is employed to distinguish a peak point based on the selected features. …”
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  8. 8
    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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  9. 9
    Classification of left/right hand movement from EEG signal by intelligent algorithms

    Classification of left/right hand movement from EEG signal by intelligent algorithms by Baig, M.Z., Javed, E., Ayaz, Y., Afzal, W., Gillani, S.O., Naveed, M., Jamil, M.

    Published 2015
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  10. 10
    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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  11. 11
    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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  12. 12
    Classification of EEG Spectrogram Using ANN for IQ Application

    Classification of EEG Spectrogram Using ANN for IQ Application by Mahfuzah, Mustafa, Norizam, Sulaiman

    Published 2013
    “… The intelligence term can be view in many areas such as linguistic, mathematical, music and art. …”
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  13. 13
    An enhanced computational model based on social spider optimisation algorithm for EEG- based emotion recognition

    An enhanced computational model based on social spider optimisation algorithm for EEG- based emotion recognition by Al-Qammaz, Abdullah Yousef Awwad

    Published 2019
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  14. 14
    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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  15. 15
    EEG Spectrogram Classification Employing ANN for IQ Application

    EEG Spectrogram Classification Employing ANN for IQ Application by Mahfuzah, Mustafa, Mohd Nasir, Taib, Sahrim, Lias, Zunairah, Murat, Norizam, Sulaiman

    Published 2013
    “…Then, Principal Component Analysis (PCA) is used to reduce the big matrix, and is followed with the classification of the EEG spectrogram image in IQ application using ANN algorithm. The results are then validated based on the concept of Raven's Standard Progressive Matrices (RPM) IQ test. …”
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  16. 16
    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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  17. 17
    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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  18. 18
    What, how and when to use knowledge in neural network application

    What, how and when to use knowledge in neural network application by Wan Ishak, Wan Hussain, Abdul Rahman, Shuzlina

    Published 2004
    “…Neural network is one of the well-known artificial intelligence techniques. Neural Networks attempt to bring computers a little closer to the brain's capabilities by imitating certain aspects of information processing in the brain,"i a highly simplified way.These disciplines formulate a formula to form a brain like function, called artificial neuron. …”
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  19. 19
    Beyond Sentiment Analysis: A Review of Recent Trends in Text Based Sentiment Analysis and Emotion Detection

    Beyond Sentiment Analysis: A Review of Recent Trends in Text Based Sentiment Analysis and Emotion Detection by Lai Po Hung, Suraya Alias

    Published 2023
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  20. 20
    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 second proposed system using a hybrid technology consists of two parts: the first part is the GoogLeNet, ResNet-50 and AlexNet models for extracting feature maps, while the second part is the SVM algorithm for classifying feature maps. 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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