Search Results - (((( pattern clustering algorithm ) OR ( pattern bees algorithm ))) OR ( deep learning algorithm ))

Search alternatives:

Refine Results
  1. 1
    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, Abdul Rahman, Abdul Wahab, Dzulkifli, Mariam Adawiah

    Published 2015
    “…This study aims at analyzing EEG signals for the purpose of clustering natural language morphemes using the Artificial Bee Colony (ABC) algorithm. …”
    Get full text
    Get full text
    Proceeding Paper
    Save to List
    Saved in:
  2. 2
    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
    “…This study aims at analyzing EEG signals for the purpose of clustering natural language morphemes using the Artificial Bee Colony (ABC) algorithm. …”
    Get full text
    Get full text
    Get full text
    Book Chapter
    Save to List
    Saved in:
  3. 3
    Meta-heuristics and deep learning for energy applications: Review and open research challenges (2018?2023)

    Meta-heuristics and deep learning for energy applications: Review and open research challenges (2018?2023) by Hosseini E., Al-Ghaili A.M., Kadir D.H., Gunasekaran S.S., Ahmed A.N., Jamil N., Deveci M., Razali R.A.

    Published 2025
    Subjects:
    Review
    Save to List
    Saved in:
  4. 4
    A Review of Unsupervised Machine Learning Frameworks for Anomaly Detection in Industrial Applications

    A Review of Unsupervised Machine Learning Frameworks for Anomaly Detection in Industrial Applications by Usmani, U.A., Happonen, A., Watada, J.

    Published 2022
    “…Without human input, these algorithms discover patterns or groupings in the data. …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  5. 5
    Enhancement of text representation for Indonesian document summarization with deep sequential pattern mining

    Enhancement of text representation for Indonesian document summarization with deep sequential pattern mining by Dian Sa’adillah Maylawati

    Published 2023
    “…Second, the proposed SPM approach is combined with Deep Belief Network (DBN), called DeepSPM, based on the unsupervised Deep Learning method. …”
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  6. 6
    Adaptive Feature Selection and Image Classification Using Manifold Learning Techniques

    Adaptive Feature Selection and Image Classification Using Manifold Learning Techniques by ASHRAF, AMNA, MOHD NAWI, NAZRI, MUHAMMAD AAMIR, MUHAMMAD AAMIR

    Published 2024
    “…Clustering algorithms such as K-means, spectral clustering, and the Gaussian Mixer Model have been tested with manifold learning approaches for adaptive feature selection. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  7. 7
    DC-GAN-based synthetic X-ray images augmentation for increasing the performance of EfficientNet for COVID-19 detection

    DC-GAN-based synthetic X-ray images augmentation for increasing the performance of EfficientNet for COVID-19 detection by Pir Masoom Shah, Hamid Ullah, Rahim Ullah, Dilawar Shah, Yulin Wang, Saif ul Islam, Abdullah Gani, Rodrigues, Joel J. P. C.

    Published 2021
    “…Currently, many deep learning models are being used to classify COVID‐19 and normal cases from chest X‐rays. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  8. 8
    A Data Mining Approach to Enhancing Birth and Death Registration Processes

    A Data Mining Approach to Enhancing Birth and Death Registration Processes by Erfan, Hasmin

    Published 2025
    “…Future research may explorer the integration of deep learning models for further automate the registration process and enhance predictive accuracy.…”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  9. 9
    Neural Network Training Using Hybrid Particle-move Artificial Bee Colony Algorithm for Pattern Classification

    Neural Network Training Using Hybrid Particle-move Artificial Bee Colony Algorithm for Pattern Classification by Nuaimi, Zakaria Noor Aldeen Mahmood Al, Abdullah, Rosni

    Published 2017
    “…Artificial Bees Colony (ABC) optimization algorithm is one of the competitive algorithms in the SI algorithms group. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  10. 10
    Clustering ensemble learning method based on incremental genetic algorithms

    Clustering ensemble learning method based on incremental genetic algorithms by Ghaemi, Reza

    Published 2012
    “…In the first and second phases, a threshold fuzzy c-means clustering algorithm as a clusterer and a pattern ensemble learning method based on the incremental genetic-based algorithms are proposed respectively. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  11. 11
    Neural network training using hybrid particle-move artificial bee colony algorithm for pattern classification

    Neural network training using hybrid particle-move artificial bee colony algorithm for pattern classification by Al Nuaimi, Zakaria Noor Aldeen Mahmood, Abdullah, Rosni

    Published 2017
    “…In this work, we aimed to highlight the performance of the Hybrid Particle-move Artificial Bee Colony (HPABC) algorithm by applying it on the ANNT application.The performance of the HPABC algorithm was investigated on four benchmark pattern-classification data sets and the results were compared with other algorithms.The results obtained illustrate that HPABC algorithm can efficiently be used for ANNT.HPABC outperformed the original ABC and PSO as well as other state-of-art and hybrid algorithms in terms of time, function evaluation number and recognition accuracy.…”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  12. 12
    Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition

    Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition by Leong, Shi Xiang

    Published 2017
    “…However, further study is needed in the feature extraction and clustering algorithms part as the performance of the pattern classification is still depending on the data input.…”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  13. 13
    Application of the bees algorithm to the selection features for manufacturing data

    Application of the bees algorithm to the selection features for manufacturing data by Pham, D.T, Mahmuddin, Massudi, Otri, S., Al-Jabbouli, H.

    Published 2007
    “…The Bees Algorithm is employed to select an optimal set of features for a particular pattern classification task. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  14. 14
    Nature inspired meta-heuristic algorithms for deep learning: recent progress and novel perspective

    Nature inspired meta-heuristic algorithms for deep learning: recent progress and novel perspective by Abubakar, Adamu, Ya’u Gital, Abdulsalam, Chiroma, Haruna, Rana, Nadim, Abdulhamid, Shafi’i, Muhammad, Amina Nuhu, Umar, Aishatu Yahaya

    Published 2019
    “…The deep learning architectures not exploit by the nature inspired algorithms for optimization are unveiled. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Get full text
    Proceeding Paper
    Save to List
    Saved in:
  15. 15
    Comparative performance of deep learning and machine learning algorithms on imbalanced handwritten data

    Comparative performance of deep learning and machine learning algorithms on imbalanced handwritten data by Amri, A’inur A’fifah, Ismail, Amelia Ritahani, Zarir, Abdullah Ahmad

    Published 2018
    “…However, deep learning algorithms, such as deep belief networks showed promising results in many domains, especially in image processing. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  16. 16
    Fast and Accuracy Control Chart Pattern Recognition using a New cluster-k-Nearest Neighbor

    Fast and Accuracy Control Chart Pattern Recognition using a New cluster-k-Nearest Neighbor by Brahim Belhaouari, samir

    Published 2009
    Get full text
    Get full text
    Citation Index Journal
    Save to List
    Saved in:
  17. 17
    Fast and Accuracy Control Chart Pattern Recognition using a New cluster-k-Nearest Neighbor

    Fast and Accuracy Control Chart Pattern Recognition using a New cluster-k-Nearest Neighbor by Brahim Belhaouari, samir

    Published 2008
    Get full text
    Get full text
    Citation Index Journal
    Save to List
    Saved in:
  18. 18
    A comparative study of deep learning algorithms in univariate and multivariate forecasting of the Malaysian stock market

    A comparative study of deep learning algorithms in univariate and multivariate forecasting of the Malaysian stock market by Mohd. Ridzuan Ab. Khalil, Azuraliza Abu Bakar

    Published 2023
    “…This study aims to develop a univariate and multivariate stock market forecasting model using three deep learning algorithms and compare the performance of those models. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  19. 19
    The Effect Of Linkages In The Hierarchical Clustering Of Auto-Regressive Algorithm For Defect Identification In Heat Exchanger Tubes

    The Effect Of Linkages In The Hierarchical Clustering Of Auto-Regressive Algorithm For Defect Identification In Heat Exchanger Tubes by Abd Halim, Zakiah, Jamaludin, Nordin, Putra, Azma

    Published 2019
    “…The clustering results from the ‘ward’ linkages were represented via a dendrogram showing the hidden pattern between clusters. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  20. 20
    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
    “…Fed-batch fermentation process has always been a challenge for optimisation because it is highly non-linear and complex. Deep reinforcement learning is a self-learning algorithm through trial and error and experience, without any prior knowledge. …”
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:

Search Tools: