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  1. 1
    Optimization of Multilayer Perceptron (MLP) network training algorithms for agrwood oil quality separation / Noratikah Zawani Mahabob ... [et al.]

    Optimization of Multilayer Perceptron (MLP) network training algorithms for agrwood oil quality separation / Noratikah Zawani Mahabob ... [et al.] by Mahabob, Noratikah Zawani, Mohd Yusoff, Zakiah, Ismail, Nurlaila, Taib, Mohd Nasir

    Published 2020
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  2. 2
    Sentiment classification for malay newspaper using clonal selection algorithm / Nur Fitri Nabila Mohamad Nasir

    Sentiment classification for malay newspaper using clonal selection algorithm / Nur Fitri Nabila Mohamad Nasir by Mohamad Nasir, Nur Fitri Nabila

    Published 2013
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  3. 3
    Multi objective genetic algorithm for training three term backpropagation network

    Multi objective genetic algorithm for training three term backpropagation network by Osman Ibrahim, Ashraf, Shamsuddin, Siti Mariyam, Ahmad, Nor Bahiah, Qasem, Sultan Noman

    Published 2013
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  4. 4
    Separable Recursive Training Algorithms with Switching Module

    Separable Recursive Training Algorithms with Switching Module by Asirvadam , Vijanth Sagayan

    Published 2009
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  5. 5
    Training functional link neural network with ant lion optimizer

    Training functional link neural network with ant lion optimizer by Mohmad Hassim, Yana Mazwin, Ghazali, Rozaida

    Published 2020
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  6. 6
    Dynamic training rate for backpropagation learning algorithm

    Dynamic training rate for backpropagation learning algorithm by Al-Duais, M. S., Yaakub, Abdul Razak, Yusoff, Nooraini

    Published 2013
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  7. 7
    Semantic-k-NN algorithm: An enhanced version of traditional k-NN algorithm

    Semantic-k-NN algorithm: An enhanced version of traditional k-NN algorithm by Ali, M., Jung, L.T., Abdel-Aty, A.-H., Abubakar, M.Y., Elhoseny, M., Ali, I.

    Published 2020
    “…It is aimed for general security applications such as finding (the confidentiality level of the data when the algorithm is trained with multiple training categories during the data classification phase. …”
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  8. 8
    Semantic-k-NN algorithm: An enhanced version of traditional k-NN algorithm

    Semantic-k-NN algorithm: An enhanced version of traditional k-NN algorithm by Ali, M., Jung, L.T., Abdel-Aty, A.-H., Abubakar, M.Y., Elhoseny, M., Ali, I.

    Published 2020
    “…It is aimed for general security applications such as finding (the confidentiality level of the data when the algorithm is trained with multiple training categories during the data classification phase. …”
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  9. 9
    Enhancement processing time and accuracy training via significant parameters in the batch BP algorithm

    Enhancement processing time and accuracy training via significant parameters in the batch BP algorithm by Fatma Susilawati, Mohamad, Mumtazimah, Mohamad, Sarhan, AlDuais

    Published 2020
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  10. 10
    Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process

    Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process by Ali Al-Assadi, Hayder M. A.

    Published 2004
    “…The design network is trained by presenting several target machining data that the network must learn according to a learning rule (algorithm). …”
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  11. 11
    Integrating genetic algorithms and fuzzy c-means for anomaly detection

    Integrating genetic algorithms and fuzzy c-means for anomaly detection by Chimphlee, Witcha, Abdullah, Abdul Hanan, Sap, Noor Md., Chimphlee, Siriporn, Srinoy, Surat

    Published 2005
    “…Traditional anomaly detection algorithms require a set of purely normal data from which they train their model. …”
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  12. 12
    Sentiment analysis for malay newspaper (SAMNews) using negative selection algorithm / Nur Amalina Redzuan

    Sentiment analysis for malay newspaper (SAMNews) using negative selection algorithm / Nur Amalina Redzuan by Redzuan, Nur Amalina

    Published 2013
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  13. 13
    Weight Optimization in Recurrent Neural Networks with Hybrid Metaheuristic Cuckoo Search Techniques for Data Classification

    Weight Optimization in Recurrent Neural Networks with Hybrid Metaheuristic Cuckoo Search Techniques for Data Classification by Nawi, N.M., Khan, A., Rehman, M.Z., Chiroma, H., Herawan, T.

    Published 2015
    “…The simulation results show that the computational efficiency of ERN and BPERN training process is highly enhanced when coupled with the proposed hybrid method.…”
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  14. 14
    RMIL/AG: A new class of nonlinear conjugate gradient for training back propagation algorithm

    RMIL/AG: A new class of nonlinear conjugate gradient for training back propagation algorithm by Basri, S.M.M., Nawi, N.M., Mamat, M., Hamid, N.A.

    Published 2018
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  15. 15
    Enhancement of bearing defect diagnosis via genetic algorithm optimized feature selection

    Enhancement of bearing defect diagnosis via genetic algorithm optimized feature selection by Chia, Yee Shin

    Published 2015
    “…This is due to the features selected in this classifier is over-fitted to the training data and not generalized for variations in testing data. …”
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  16. 16
    Computer based training for data structure and algorithms

    Computer based training for data structure and algorithms by Arlina Binti Abdul Razak

    Published 2026
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  17. 17
    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
    “…By optimizing the training of the neural networks using optimal weight set, better results can be obtained by the neural networks.Traditional neural networks algorithms such as Back Propagation (BP) were used for ANNT, but they have some drawbacks such as computational complexity and getting trapped in the local minima.Therefore, evolutionary algorithms like the Swarm Intelligence (SI) algorithms have been employed in ANNT to overcome such issues.Artificial Bees Colony (ABC) optimization algorithm is one of the competitive algorithms in the SI algorithms group. …”
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  18. 18
    Parallel execution of distributed SVM using MPI (CoDLib)

    Parallel execution of distributed SVM using MPI (CoDLib) by Salleh N.S.M., Suliman A., Ahmad A.R.

    Published 2023
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  19. 19
    Development of heuristic task scheduling algorithm in cloud computing

    Development of heuristic task scheduling algorithm in cloud computing by Diallo, Laouratou, Hassan Abdalla Hashim, Aisha, Olanrewaju, Rashidah Funke

    Published 2016
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    Proceeding Paper
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  20. 20
    Shape-based recognition using combined Jaccard and Mahalanobis measurement / Noor Aznimah Abdul Aziz

    Shape-based recognition using combined Jaccard and Mahalanobis measurement / Noor Aznimah Abdul Aziz by Abdul Aziz, Noor Aznimah

    Published 2013
    “…Numerous well-established shape recognition approaches for handling variance of image transformations and strokes variations in free-hand digital sketching environment but none has satisfactorily deal with object features yet. Complexity in the computation measure, expensive in computation time, requires large training data set and extensive training is not practical, especially in sketching recognition. …”
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