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  1. 1
    Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly

    Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

    Published 2019
    “…All the algorithm for the engine has been developed by using Java script language. …”
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  2. 2
    Algorithm As A Problem Solving Technique For Teaching And Learning Of The Malay Language

    Algorithm As A Problem Solving Technique For Teaching And Learning Of The Malay Language by Jano, Zanariah, Omar, Norliza, Nazir, Faridah

    Published 2019
    “…This conceptual teaching and learning algorithm was conducted in five steps namely the induction set; step 1; step 2; step 3; and enrichment and recovery. …”
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  3. 3
    Algorithm as a problem solving technique for teaching and learning of the Malay language

    Algorithm as a problem solving technique for teaching and learning of the Malay language by Faridah Nazir, Zanariah Jano, Norliza Omar

    Published 2019
    “…This conceptual teaching and learning algorithm was conducted in five steps namely the induction set; step 1; step 2; step 3; and enrichment and recovery. …”
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  4. 4
    Algorithm as a problem solving technique for teaching and learning of the Malay language

    Algorithm as a problem solving technique for teaching and learning of the Malay language by Nazir, Faridah, Jano, Zanariah, Omar, Norliza

    Published 2019
    “…This conceptual teaching and learning algorithm was conducted in five steps namely the induction set; step 1; step 2; step 3; and enrichment and recovery. …”
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  5. 5
    Algorithm animation for cryptanalysis of caesar and hill ciphers / Sapiee Haji Jamel and Giuseppina Sherry Sayan

    Algorithm animation for cryptanalysis of caesar and hill ciphers / Sapiee Haji Jamel and Giuseppina Sherry Sayan by Jamel, Shafie, Sayan, Giuseppina Sherry

    Published 2009
    “…This new trend gives an advantage to cryptanalyst since types of algorithm(s) used are no longer a secret. Cryptanalysis steps can be easily explained using algorithm animation that can be easily integrated with any e-learning platform. …”
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  6. 6
    Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof

    Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof by Yusof, Yusman

    Published 2019
    “…From the reviews, it is evident that autonomous system is set to handle finite number of encountered states using finite sequences of actions. In order to learn the optimized states-action policy the self-learning algorithm is developed using hybrid AI algorithm by combining unsupervised weightless neural network, which employs AUTOWiSARD and reinforcement learning algorithm, which employs Q-learning. …”
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  7. 7
    Multi-step time series prediction using recurrent kernel online sequential extreme learning machine / Liu Zongying

    Multi-step time series prediction using recurrent kernel online sequential extreme learning machine / Liu Zongying by Liu , Zongying

    Published 2019
    “…However, the problems with traditional offline and online learning algorithms in machine learning algorithms are usually faced with parameter dependency, concept drift handling problem, connectionless of neural net and unfixed reservoir. …”
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  8. 8
    Artificial intelligent integrated into sun-tracking system to enhance the accuracy, reliability and long-term performance in solar energy harnessing

    Artificial intelligent integrated into sun-tracking system to enhance the accuracy, reliability and long-term performance in solar energy harnessing by Tan, Jun You

    Published 2022
    “…The proposed AI algorithm integrates two deep learning models which are object detection algorithm and reinforcement learning. …”
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  9. 9
    Optimal route checking using genetic algorithm for UiTM's bus services / Tengku Salman Fathi Tengku Jaafar

    Optimal route checking using genetic algorithm for UiTM's bus services / Tengku Salman Fathi Tengku Jaafar by Tengku Jaafar, Tengku Salman Fathi

    Published 2006
    “…Although from human logical thinking, the route can be generated easily but the calculation of checking the route whether it is optimal route or not is difficult and will take long time to be implemented. This research study with the development of the Optimal Route Checking Using Genetic Algorithm system should solve this scenario. …”
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  10. 10
    Autism Spectrum Disorder Classification Using Deep Learning

    Autism Spectrum Disorder Classification Using Deep Learning by Abdulrazak Yahya, Saleh, Lim Huey, Chern

    Published 2021
    “…Recently, deep learning methods have significantly sharpened the cutting edge of learning algorithms in a wide range of artificial intelligence tasks. …”
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  11. 11
    Using Pattern Matching technique for feature recognition of STEP file

    Using Pattern Matching technique for feature recognition of STEP file by Nik Norhazlina Nik Hassan

    Published 2008
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    Learning Object
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  12. 12
    Optimizing high-density aquaculture rotifer Detection using deep learning algorithm

    Optimizing high-density aquaculture rotifer Detection using deep learning algorithm by Alixson Polumpung, Kit Guan Lim, Min Keng Tan, Sitti Raehanah Muhamad Shaleh, Renee Ka Yin Chin, Kenneth Teo Tze Kin

    Published 2022
    “…Second, is to develop the deep learning algorithm based on YOLOv3. Third step is to training and evaluate the model using loss function. …”
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  13. 13
    Attacks detection in 6G wireless networks using machine learning

    Attacks detection in 6G wireless networks using machine learning by Saeed, Mamoon M., Saeed, Rashid A., Gaid, Abdulguddoos S. A., Mokhtar, Rania A., Khalifa, Othman Omran, Ahmed, Zeinab E.

    Published 2023
    “…The Attacks Detection in 6G (AD6Gs) wireless networks created by this research uses a Machine Learning (ML) algorithm. The pre-processing stage of the ML-AD6Gs process is the initial step. …”
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  14. 14
    Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm

    Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm by Al-Jumaili A.H.A., Muniyandi R.C., Hasan M.K., Singh M.J., Paw J.K.S., Al-Jumaily A.

    Published 2025
    “…The results showed that using canopy as a preprocessing step cut the time it proceeds to deal with the significant number of power load abnormalities found in parallel using a fast density peak dataset and the time it proceeds for the k-means algorithm to run. …”
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  15. 15
    Opposition-based learning simulated kalman filter for Numerical optimization problems

    Opposition-based learning simulated kalman filter for Numerical optimization problems by Mohd Falfazli, Mat Jusof

    Published 2016
    “…Using CEC2014 benchmark suite, it is found that the SKF with opposition-based learning outperforms the original SKF algorithm in most cases. …”
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    Research Book Profile
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  16. 16
    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
    “…These problems will occur because these fields are mainly used machine learning classifiers. However, machine learning accuracy is affected by the noisy and irrelevant features. …”
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  17. 17
    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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  18. 18
    A comparative analysis of machine learning algorithms for diabetes prediction

    A comparative analysis of machine learning algorithms for diabetes prediction by Alansari, Waseem Abdulmahdi, Masnizah Mohd

    Published 2024
    “…The results indicate that pre-processing steps and dataset characteristics significantly impact algorithm performance. …”
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  19. 19
    A step towards the development of VHDL model for ANN based EMG signal classifier

    A step towards the development of VHDL model for ANN based EMG signal classifier by Ahsan, Md. Rezwanul, Ibrahimy, Muhammad Ibn, Khalifa, Othman Omran

    Published 2012
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  20. 20
    Wavelet network based online sequential extreme learning machine for dynamic system modeling

    Wavelet network based online sequential extreme learning machine for dynamic system modeling by Mohammed Salih, Dhiadeen, Mohd Noor, Samsul Bahari, Marhaban, Mohammad Hamiruce, Raja Ahmad, Raja Mohd Kamil

    Published 2013
    “…The main advantage of OSELM over conventional algorithms is the ability of updating network weights sequentially through data sample-by-sample in a single learning step. …”
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