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  1. 1
    Ant colony optimization algorithm for load balancing in grid computing

    Ant colony optimization algorithm for load balancing in grid computing by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

    Published 2012
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    Monograph
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  2. 2
    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing

    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

    Published 2011
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    Thesis
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  3. 3
    Resource management in grid computing using ant colony optimization

    Resource management in grid computing using ant colony optimization by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

    Published 2011
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  4. 4
    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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    Working Paper
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  5. 5
    Supervised deep learning algorithms for process fault detection and diagnosis under different temporal subsequence length of process data

    Supervised deep learning algorithms for process fault detection and diagnosis under different temporal subsequence length of process data by Terence Chia Yi Kai, Agus Saptoro, Zulfan Adi Putra, King Hann Lim, Wan Sieng Yeo, Jaka Sunarso

    Published 2025
    “…Deep learning algorithms were widely used among all the data-driven algorithms. …”
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  6. 6
    Wavelet neural networks based solutions for elliptic partial differential equations with improved butterfly optimization algorithm training

    Wavelet neural networks based solutions for elliptic partial differential equations with improved butterfly optimization algorithm training by Lee, Sen Tan, Zainuddin, Zarita, Ong, Pauline

    Published 2020
    “…Although the gradient information of the commonly used gradient descent training algorithm in WNNs may direct the search to optimal weight solutions that minimize the error function, the learning process is slow due to the complex calculation of the partial derivatives. …”
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  7. 7
    A Reference Based Surface Defect Segmentation Algorithm For Automatic Optical Inspection System

    A Reference Based Surface Defect Segmentation Algorithm For Automatic Optical Inspection System by Wong, Ze-Hao

    Published 2020
    “…However, present complex algorithms which are accurate require high processing power using a large size of learning dataset without labelling error. …”
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  8. 8
    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
    “…This will make the learning process simpler and more convenient in practice. …”
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    Proceeding Paper
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  9. 9
    Data Analysis and Machine Learning Algorithms Evaluation for Bioliq AI-based Predictive Tool

    Data Analysis and Machine Learning Algorithms Evaluation for Bioliq AI-based Predictive Tool by Samuel Simbine, Augusto

    Published 2019
    “…The mass production hasn’t initiated due to the inefficiency of the process and the dependency on experts. EDI GmbH in collaboration with Karlsruhe Institute of Technology (KIT) are working on the solution (AI-based tool for predictive process optimization for chemical plants) for the above-mentioned problem. …”
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    Final Year Project
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  10. 10
    Machine Learning Algorithms for Diabetes Prediction: A Review Paper

    Machine Learning Algorithms for Diabetes Prediction: A Review Paper by Al-Sideiri A., Cob Z.B.C., Drus S.B.M.

    Published 2023
    Conference Paper
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  11. 11
    Waste management using machine learning and deep learning algorithms

    Waste management using machine learning and deep learning algorithms by Sami, Khan Nasik, Amin, Zian Md Afique, Hassan, Raini

    Published 2020
    “…For our research we did the comparisons between three Machine Learning algorithms, namely Support Vector Machine (SVM), Random Forest, and Decision Tree, and one Deep Learning algorithm called Convolutional Neural Network (CNN), to find the optimal algorithm that best fits for the waste classification solution. …”
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  12. 12
    A Chaotic Teaching Learning Based Optimization Algorithm for Optimization Emergency Flood Evacuation Routing

    A Chaotic Teaching Learning Based Optimization Algorithm for Optimization Emergency Flood Evacuation Routing by Kamal Z., Zamli

    Published 2016
    “…Unlike competing work, the proposed work dwells on TLBO as parameter free algorithm (i.e. free from tuning). In this manner, the results reflect the actual algorithm’s optimal performance without the necessity of painstakingly difficult tuning process that potentially leads to false optimum solution. …”
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  13. 13
    Accelerating learning performance of back propagation algorithm by using adaptive gain together with adaptive momentum and adaptive learning rate on classification problems

    Accelerating learning performance of back propagation algorithm by using adaptive gain together with adaptive momentum and adaptive learning rate on classification problems by Abdul Hamid, Norhamreeza, Mohd Nawi, Nazri, Ghazali, Rozaida, Mohd Salleh, Mohd Najib

    Published 2011
    “…Over the years, many improvements and modifications of the back propagation learning algorithm have been reported. In this research, we propose a new modified back propagation learning algorithm by introducing adaptive gain together with adaptive momentum and adaptive learning rate into weight update process. …”
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  14. 14
    An energy-efficient spectrum-aware reinforcement learning-based clustering algorithm for cognitive radio sensor networks

    An energy-efficient spectrum-aware reinforcement learning-based clustering algorithm for cognitive radio sensor networks by Mustapha, Ibrahim, Mohd Ali, Borhanuddin, A. Rasid, Mohd Fadlee, Sali, Aduwati, Mohamad, Hafizal

    Published 2015
    “…The problem of selecting an optimal cluster is formulated as a Markov Decision Process (MDP) in the algorithm and the obtained simulation results show convergence, learning and adaptability of the algorithm to dynamic environment towards achieving an optimal solution. …”
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  15. 15
    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
    “…Artificial Neural Network (ANN) was selected from Machine Learning Algorithms to be the learning algorithm. …”
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  16. 16
    Concrete surface inspection by using unmanned aerial vehicle (UAV) and deep learning algorithms YOLOv7 / Saffa Nasuha Rusdinadi

    Concrete surface inspection by using unmanned aerial vehicle (UAV) and deep learning algorithms YOLOv7 / Saffa Nasuha Rusdinadi by Rusdinadi, Saffa Nasuha

    Published 2024
    “…This research aims to improve the detection and analysis of cracks on concrete surfaces by utilizing UAVs and yolo algorithms. Uavs offer a versatile and cost-effective solution for capturing high-resolution orthophotos of large and hard-to-reach concrete structures. …”
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  17. 17
    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
    “…Computational thinking or CT refers to the thought processes involved in expressing solutions as computational steps or algorithms that can be carried out by a computer. …”
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  18. 18
    Coalition of genetic algorithms and artificial neural network for isolated spoken Malay speech recognition / Noraini Seman

    Coalition of genetic algorithms and artificial neural network for isolated spoken Malay speech recognition / Noraini Seman by Seman, Noraini

    Published 2012
    “…However, due to the stochastic nature of this algorithm, the learning process can reach an optimal solution with much higher probability than many standard neural network techniques.…”
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  19. 19
    Underwater Image Recognition using Machine Learning

    Underwater Image Recognition using Machine Learning by Divya, N.K., Manjula, Sanjay Koti, Priyadarshini, S

    Published 2024
    “…A Convolutional Neural Network (CNN) is a type of a deep learned an algorithm that has been created for image processing when using convolutional layers to automatically and in a hierarchical way learn features from the input images. …”
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  20. 20
    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
    “…Computational thinking or CT refers to the thought processes involved in expressing solutions as computational steps or algorithms that can be carried out by a computer. …”
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