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  1. 1
    Cloud-based lightweight detection of hardhat compliance based on YOLOv5 in power construction site

    Cloud-based lightweight detection of hardhat compliance based on YOLOv5 in power construction site by Wanbo, Luo

    Published 2025
    “…Therefore, this thesis explores and studies public hardhat datasets, deep learning algorithms, power Internet of Things (PIoT), and edge computing to address the above issues. …”
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  2. 2
    Queue Management Performance Evaluation of REM, GRED, and DropTail Algorithms

    Queue Management Performance Evaluation of REM, GRED, and DropTail Algorithms by Khudhur, Fadi Hani

    Published 2012
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  3. 3
    Dropping down the maximum item set: improving the stylometric authorship attribution algorithm in the text mining for authorship investigation

    Dropping down the maximum item set: improving the stylometric authorship attribution algorithm in the text mining for authorship investigation by Mustafa, Tareef Kamil, Mustapha, Norwati, Azmi Murad, Masrah Azrifah, Sulaiman, Md. Nasir

    Published 2010
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  4. 4
    Comparative study of meta-heuristics optimization algorithm using benchmark function

    Comparative study of meta-heuristics optimization algorithm using benchmark function by Ismail, I., Halim, A.H.

    Published 2017
    “…Despite of the good performance, there is limitation in some algorithms that deteriorates by certain degree of problem type. …”
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  5. 5
    Effect of chaos noise on the learning ability of back propagation algorithm in feed forward neural network

    Effect of chaos noise on the learning ability of back propagation algorithm in feed forward neural network by Azian Azamimi, Uwate, Yoko, Nishio, Yoshifumi

    Published 2010
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  6. 6
    Immune-based technique for undergraduate programmes recommendation / Muhammad Azrill Mohd Zamri

    Immune-based technique for undergraduate programmes recommendation / Muhammad Azrill Mohd Zamri by Mohd Zamri, Muhammad Azrill

    Published 2017
    “…The right determination of an undergraduate programme selection by applicants is not an easy task. Some applicants who enrolled for unsuitable programme ended up failed to progress or dropped out from the programme. …”
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  7. 7
    A modified generalized RBF model with EM-based learning algorithm for medical applications

    A modified generalized RBF model with EM-based learning algorithm for medical applications by Ma, Li Ya, Abdul Rahman, Abdul Wahab, Quek, Chai

    Published 2006
    “…Radial Basis Function (RBF) has been widely used in different fields, due to its fast learning and interpretability of its solution. …”
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  8. 8
    SLIDING WINDOW TRAINING ALGORITHMS USING MLP-NETWORK FOR CORRELATED AND LOST PACKET DATA

    SLIDING WINDOW TRAINING ALGORITHMS USING MLP-NETWORK FOR CORRELATED AND LOST PACKET DATA by AHMED IZZELDIN, HUZAIFA TAWFEIG

    Published 2012
    “…This thesis gives a systematic investigation of various MLP learning mainly Sliding Window (SW) learning mode which is treated as the adaptation of offline algorithms into online application Consequently this thesis reviews various offline algorithms including: batch backpropagation, nonlinear conjugate gradient, limited memory and full-memory Broyden, Fletcher, Goldfarb and Shanno algorithms and different forms of the latest proposed bimary ensemble learning. …”
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  9. 9
    Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection

    Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection by Tubishat, Mohammad, Idris, Norisma, Shuib, Liyana, Abushariah, Mohammad A.M., Mirjalili, Seyedali

    Published 2020
    “…Two main improvements were included into the original SSA algorithm to alleviate its drawbacks and adapt it for feature selection problems. …”
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  10. 10
    Q-learning whale optimization algorithm for test suite generation with constraints support

    Q-learning whale optimization algorithm for test suite generation with constraints support by Hassan, Ali Abdullah, Salwani, Abdullah, Kamal Z., Zamli, Rozilawati, Razali

    Published 2023
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  11. 11
    Token based path allocation approach for mobile robots in sorting centre for achieving high throughput

    Token based path allocation approach for mobile robots in sorting centre for achieving high throughput by Khoo, Zong Zheng

    Published 2024
    “…Thus, it is crucial to guaranteed that these robots avoid collisions and deadlocks among each other while executing tasks. There are some previous approaches that provides different sets of assumptions on the road systems, planning algorithms and layouts. …”
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  12. 12
    Ensemble dual recursive learning algorithms for identifying flow with leakage

    Ensemble dual recursive learning algorithms for identifying flow with leakage by Akib, Afifi, Saad , Nordin, Asirvadam , Vijanth Sagayan

    Published 2010
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  13. 13
    Active force control with iterative learning control algorithm for a vehicle suspension

    Active force control with iterative learning control algorithm for a vehicle suspension by Rosmazi, Rosli

    Published 2013
    “…The research focuses on the application of an active force control (AFC) strategy with iterative learning control (ILC) algorithms to compensate for the various introduced road profiles or 'disturbances' in a quarter car suspension system as an improvement to ride comfort performance. …”
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  14. 14
    Learning Algorithm effect on Multilayer Feed Forward Artificial Neural Network performance in image coding

    Learning Algorithm effect on Multilayer Feed Forward Artificial Neural Network performance in image coding by Mahmoud, Omer, Anwar, Farhat, Salami, Momoh Jimoh Emiyoka

    Published 2007
    “…The essence of this study is to investigate the most efficient and effective training methods for use in image compression and its subsequent applications. The obtained results show that the Quasi-Newton based algorithm has better performance as compared to the other two algorithms.…”
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  15. 15
    FASTA-ELM: a fast adaptive shrinkage/thresholding algorithm for extreme learning machine and its application to gender recognition

    FASTA-ELM: a fast adaptive shrinkage/thresholding algorithm for extreme learning machine and its application to gender recognition by Mahmood, Saif F., Marhaban, Mohammad Hamiruce, Rokhani, Fakhrul Zaman, Samsudin, Khairulmizam, Arigbabu, Olasimbo Ayodeji

    Published 2017
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  16. 16
    The delay with new-additive increase multiplicative decrease congestion avoidance and control algorithm.

    The delay with new-additive increase multiplicative decrease congestion avoidance and control algorithm. by Jasem, Hayder Natiq, Ahmad Zukarnain, Zuriati, Mohamed, Othman, Subramaniam, Shamala

    Published 2010
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  17. 17
    Machine learning: tasks, modern day applications and challenges

    Machine learning: tasks, modern day applications and challenges by Aljuaid, Lamyaa Zaed, Koh, Tieng Wei, Sharif, Khaironi Yatim

    Published 2019
    “…Machine learning algorithms learned from available data. Further, this learning laid the foundation to develop AI for the various systems around us. …”
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  18. 18
    Enhanced Adaptive Confidence-Based Q Routing Algorithms For Network Traffic

    Enhanced Adaptive Confidence-Based Q Routing Algorithms For Network Traffic by Yap, Soon Teck

    Published 2004
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  19. 19
    Global-Local Partial Least Squares Discriminant Analysis And Its Extension In Reproducing Kernel Hilbert Space

    Global-Local Partial Least Squares Discriminant Analysis And Its Extension In Reproducing Kernel Hilbert Space by Muhammad, Aminu

    Published 2021
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  20. 20
    Optimal parameters of an ELM-based interval type 2 fuzzy logic system: a hybrid learning algorithm

    Optimal parameters of an ELM-based interval type 2 fuzzy logic system: a hybrid learning algorithm by Hassan, S., Khanesar, M.A., Jaafar, J., Khosravi, A.

    Published 2018
    “…Type 2 fuzzy logic system has more parameters than the type 1 fuzzy logic system and is therefore much more complex than its counterpart. This paper proposes optimal parameters for an extreme learning machine-based interval type 2 fuzzy logic system to learn its best configuration. …”
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