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  1. 1
    Development of an artificial neural network algorithm for predicting the cutting force in end milling of Inconel 718 alloy

    Development of an artificial neural network algorithm for predicting the cutting force in end milling of Inconel 718 alloy by Hossain, Ishtiaq, Amin, A. K. M. Nurul, Patwari, Muhammed Anayet Ullah

    Published 2011
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  2. 2
    Machine learning model to predict the contact of angle using mineralogy, TOC and process parameters in shale

    Machine learning model to predict the contact of angle using mineralogy, TOC and process parameters in shale by Ameenuddin Irfan, S., Fadhli, M.Z., Padmanabhan, E.

    Published 2021
    “…The application aims to develop a machine learning program using the algorithm of Support Vector Machine or Gaussian Process Regression to successfully predict the contact angle. …”
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  3. 3
    Control of a robot arm using iterative learning algorithm with a stopping criterion

    Control of a robot arm using iterative learning algorithm with a stopping criterion by Mailah, Musa, Chong, Jonathan Wun Shiung

    Published 2002
    “…The study introduces the Active Force Control and Iterative Learning Algorithm (AFCAIL) scheme with an improved feature in the form of a suitably designed stopping criterion incorporated in the control strategy. …”
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  4. 4
    Financial time series predicting using machine learning algorithms

    Financial time series predicting using machine learning algorithms by Tiong, Leslie Ching Ow *

    Published 2013
    “…In the second proposed framework, Linear Regression Line (LRL) is utilised to identify the trend patterns from historical financial time series, which is supported by ANN and SVM for classification process separately. Subsequently, Dynamic Time Warping (DTW) algorithm is utilised through brute force to predict the trend movement. …”
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  5. 5
    Adaptive Linear System Identification over Simulated Wireless Environment

    Adaptive Linear System Identification over Simulated Wireless Environment by Elamin, Musab Jabralla Omer Elamin

    Published 2009
    “…The work looks thoroughly on three forms of instantaneous learning algorithms which are: first order algorithms (e.g. least mean square (LMS)), second order algorithms (e.g. …”
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  6. 6
    Classification models for higher learning scholarship award decisions

    Classification models for higher learning scholarship award decisions by Wirawati Dewi Ahmad, Azuraliza Abu Bakar

    Published 2018
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  7. 7
    ICS cyber attack detection with ensemble machine learning and DPI using cyber-Kit datasets

    ICS cyber attack detection with ensemble machine learning and DPI using cyber-Kit datasets by Mubarak, Sinil, Habaebi, Mohamed Hadi, Islam, Md. Rafiqul, Khan, Sheroz

    Published 2021
    “…The processed metadata is normalized for the easiness of algorithm analysis and modelled with machine learning-based latest deep learning ensemble LSTM algorithms for anomaly detection. …”
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  8. 8
    Developing framework for natphoric computer-aided web-based kansei engineering / Mohammad Bakri Che Haron

    Developing framework for natphoric computer-aided web-based kansei engineering / Mohammad Bakri Che Haron by Che Haron, Mohammad Bakri

    Published 2013
    “…The Natphoric algorithm learns the process done by training with sets of training data from previous KE research works. …”
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  9. 9
    Landslides susceptibility using Fuzzy Logic approach at Kg Iboi, Baling, Kedah / Mohd Ashraf Ahmad Zubir

    Landslides susceptibility using Fuzzy Logic approach at Kg Iboi, Baling, Kedah / Mohd Ashraf Ahmad Zubir by Ahmad Zubir, Mohd Ashraf

    Published 2023
    “…This process further extends to data processing for image recognition, culminating in the evaluation of the efficacy of the fuzzy model algorithm. …”
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    Student Project
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  10. 10
    Artificial neural network algorithm for predicting the surface roughness in end milling of Inconel 718 alloy

    Artificial neural network algorithm for predicting the surface roughness in end milling of Inconel 718 alloy by Hossain, Mohammad Ishtiyaq, Amin, A. K. M. Nurul, Patwari, Muhammed Anayet Ullah

    Published 2011
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  11. 11
    Multistage quality control in manufacturing process using blockchain with machine learning technique

    Multistage quality control in manufacturing process using blockchain with machine learning technique by Gu, J., Zhao, L., Yue, X., Arshad, N.I., Mohamad, U.H.

    Published 2023
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  12. 12
    Artificial Intelligence Integration in Mobile Applications: Innovation and Challenges in Supporting Quran Memorization and Review

    Artificial Intelligence Integration in Mobile Applications: Innovation and Challenges in Supporting Quran Memorization and Review by Khairulnazrin Nasir, Rahim Kamarul Zaman, Ahmad Bazli Ahmad Hilmi, Abdul Hakim Mahadzir, Ahmad Mukhlis bin Mustaffa

    Published 2025
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  13. 13
    Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check

    Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check by Abd Halim, Suhaila, Yupiter H. P. Manurung, Yupiter H. P. Manurung, Raziq, Muhamad Aiman, ChengYee Low, ChengYee Low, Rohmad, Muhammad Saufy, John R. C. Dizon, John R. C. Dizon, Vladimir S. Kachinskyi, Vladimir S. Kachinskyi

    Published 2023
    “…A supervised learning algorithm implemented in standard backpropagation neural network gradient descent (GD), stochastic gradient descent (SGD) and Levenberg–Marquardt (LM) was constructed using TensorFlow with Spyder IDE in python language. …”
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  14. 14
    Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check

    Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check by Abd Halim, Suhaila, Yupiter H. P. Manurung, Yupiter H. P. Manurung, Muhamad Aiman Raziq, Muhamad Aiman Raziq, ChengYee Low, ChengYee Low, Rohmad, Muhammad Saufy, John R. C. Dizon, John R. C. Dizon, Vladimir S. Kachinskyi, Vladimir S. Kachinskyi

    Published 2023
    “…A supervised learning algorithm implemented in standard backpropagation neural network gradient descent (GD), stochastic gradient descent (SGD) and Levenberg–Marquardt (LM) was constructed using TensorFlow with Spyder IDE in python language. …”
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  15. 15
    Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check

    Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check by Abd Halim, Suhaila, Yupiter H. P. Manurung, Yupiter H. P. Manurung, Raziq, MuhamadAiman, ChengYee Low, ChengYee Low, Rohmad, Muhammad Saufy, John R. C. Dizon, John R. C. Dizon, Vladimir S. Kachinskyi, Vladimir S. Kachinskyi

    Published 2023
    “…A supervised learning algorithm implemented in standard backpropagation neural network gradient descent (GD), stochastic gradient descent (SGD) and Levenberg–Marquardt (LM) was constructed using TensorFlow with Spyder IDE in python language. …”
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  16. 16
    Quality prediction and classifcation of resistance spot weld using artifcial neural networkbwith open‑sourced, self‑executable andGUI‑based application tool Q‑Check

    Quality prediction and classifcation of resistance spot weld using artifcial neural networkbwith open‑sourced, self‑executable andGUI‑based application tool Q‑Check by Abd Halim, Suhaila, H. P. Manurung, Yupiter, Raziq, Muhamad Aiman, ChengYee Low, ChengYee Low, Rohmad, Muhammad Saufy, John R. C. Dizon6 & Vladimir S. Kachinskyi, John R. C. Dizon6 & Vladimir S. Kachinskyi

    Published 2023
    “…A supervised learning algorithm implemented in standard backpropagation neural network gradient descent (GD), stochastic gradient descent (SGD) and Levenberg–Marquardt (LM) was constructed using TensorFlow with Spyder IDE in python language. …”
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  17. 17
    Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check

    Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check by SuhailaAbd Halim, SuhailaAbd Halim, Yupiter H. P. Manurung, Yupiter H. P. Manurung, Raziq, Muhamad Aiman, ChengYee Low, ChengYee Low, Rohmad, Muhammad Saufy, John R. C. Dizon, John R. C. Dizon, Vladimir S. Kachinsky, Vladimir S. Kachinsky

    Published 2023
    “…A supervised learning algorithm implemented in standard backpropagation neural network gradient descent (GD), stochastic gradient descent (SGD) and Levenberg–Marquardt (LM) was constructed using TensorFlow with Spyder IDE in python language. …”
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  18. 18
    Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check

    Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check by Abd Halim, Suhaila, Yupiter H. P. Manurung, Yupiter H. P. Manurung, Raziq, Muhamad Aiman, ChengYee Low, ChengYee Low, Rohmad, Muhammad Saufy, John R. C. Dizon, John R. C. Dizon, Vladimir S. Kachinsky, Vladimir S. Kachinsky

    Published 2023
    “…A supervised learning algorithm implemented in standard backpropagation neural network gradient descent (GD), stochastic gradient descent (SGD) and Levenberg–Marquardt (LM) was constructed using TensorFlow with Spyder IDE in python language. …”
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  19. 19
    Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check

    Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check by Abd Halim, Suhaila, Yupiter H. P. Manurung, Yupiter H. P. Manurung, Raziq, Muhamad Aiman, ChengYee Low, ChengYee Low, Rohmad, Muhammad Saufy, John R. C. Dizon, John R. C. Dizon, Vladimir S. Kachinsky, Vladimir S. Kachinsky

    Published 2023
    “…A supervised learning algorithm implemented in standard backpropagation neural network gradient descent (GD), stochastic gradient descent (SGD) and Levenberg–Marquardt (LM) was constructed using TensorFlow with Spyder IDE in python language. …”
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  20. 20
    Enhanced faster region-based convolutional neural network for oil palm tree detection

    Enhanced faster region-based convolutional neural network for oil palm tree detection by Liu, Xinni

    Published 2021
    “…To overcome this problem, researchers proposed automatic counting methods based on machine learning and image processing. However, traditional machine learning and image processing methods used handcrafted feature extraction methods. …”
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