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  1. 1

    A review of machine vision pose measurement by Xiaoxiao, Wang, Beng, Ng Seng, O. K. Rahmat, Rahmita Wirza, Sulaima, Puteri Suhaiza

    Published 2024
    “…Discusses the factors that affect the accuracy and reliability of machine vision pose measurement algorithms. …”
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    Article
  2. 2

    A review of machine vision pose measurement by Xiaoxiao, Wang, Beng, Ng Seng, O. K. Rahmat, Rahmita Wirza, Sulaima, Puteri Suhaiza

    Published 2024
    “…Discusses the factors that affect the accuracy and reliability of machine vision pose measurement algorithms. …”
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    Article
  3. 3
  4. 4

    Prediction models of heritage building based on machine learning / Nur Shahirah Ja'afar by Ja'afar, Nur Shahirah

    Published 2021
    “…These algorithms were developed by using prewar shophouses dataset from 2004 until 2018 based on factors of heritage properties. …”
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    Thesis
  5. 5

    Prediction of hydropower generation via machine learning algorithms at three Gorges Dam, China by Sattar Hanoon M., Najah Ahmed A., Razzaq A., Oudah A.Y., Alkhayyat A., Feng Huang Y., kumar P., El-Shafie A.

    Published 2024
    “…Therefore, this study investigates the capability of various machine learning algorithms in predicting the power production of a reservoir located in China using data from 1979 to 2016. …”
    Article
  6. 6

    Optimization of chest X-ray exposure factors using machine learning algorithm by Hamd, Zuhal Y., Alrebdi, H.I., Osman, Eyas G., Awwad, Areej, Alnawwaf, Layan, Nashri, Nawal, Alfnekh, Rema, Khandaker, Mayeen Uddin *

    Published 2023
    “…In this study, the chest X-ray exposure factors for 178 patients with different body mass index (BMI) values have been analyzed using the Python Machine Learning algorithm. …”
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    Article
  7. 7

    Comparison of machine learning algorithms for estimating mangrove age using sentinel 2A at Pulau Tuba, Kedah, Malaysia / Fareena Faris Francis Singaram by Faris Francis Singaram, Fareena

    Published 2021
    “…Therefore, this study aimed to used OBIA method with selected machine learning algorithm to estimate the mangrove age by using Sentinel 2A image. …”
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    Thesis
  8. 8

    Reverse migration prediction model based on machine learning / Azreen Anuar by Anuar, Azreen

    Published 2024
    “…A significant way to minimize the errors is by using a machine learning approach that can predict reverse migration intelligently depending on the tested dataset. …”
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    Thesis
  9. 9

    Neural Network Multi Layer Perceptron Modeling For Surface Quality Prediction in Laser Machining by Sivarao, Subramonian

    Published 2009
    “…One such method is machine learning, which involves using a computer algorithm to capture hidden knowledge from data. …”
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    Book Chapter
  10. 10

    Optimization of cutting parameters to minimize tooling cost in high speed turning of SS304 using coated carbide tool using genetic algorithm method by Al Hazza, Muataz Hazza Faizi, Mohmad Bakhari, Nur Amirah Najwa

    Published 2016
    “…The experiments were designed using Box Behnken Design (BBD) with three input factors: cutting speed, feeding speed and depth of cut and three machining levels.…”
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    Article
  11. 11

    Prediction of life expectancy for Asian population using machine learning ALGORITHMS / Nurul Shahira Pisal, Shuzlina Abdul-Rahman, Mastura Hanafiah and Saidatul Izyanie Kamarudin by Pisal, Nurul Shahira, Abdul Rahman, Shuzlina, Hanafiah, Mastura, Kamarudin, Saidatul Izyanie

    Published 2022
    “…However, studies focusing on the Asian population are limited. This study presents machine learning algorithms for life expectancy based on the Asian population dataset. …”
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    Article
  12. 12

    Tree-based machine learning in classifying reverse migration/ Azreen Anuar, Nur Huzeima Mohd Hussain and Hugh Byrd by Anuar, Azreen, Mohd Hussain, Nur Huzeima, Byrd, Hugh

    Published 2023
    “…With the use of appropriate machine learning algorithms, policymakers and stakeholders can make more informed decisions to address the challenges posed by reverse migration.…”
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    Article
  13. 13

    Early prediction of acute kidney injury using machine learning algorithms by Ismail, Amelia Ritahani, Abdul Aziz, Normaziah, Dzaharudin, Fatimah, Mat Ralib, Azrina, Md Nor, Norzaliza, Yahya, Norzariyah

    Published 2018
    “…The application of machine learning algorithms in the medical sector is gaining increased attention in the last few decades. …”
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    Proceeding Paper
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    Poverty risk prediction based on socioeconomic factors using machine learning approach by Mohd Zawari, Nur Farhana Adibah

    Published 2025
    “…This study seeks to develop a predictive model of measuring poverty risk using socioeconomic factors based on a machine learning framework. …”
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    Student Project
  16. 16

    Erosion Susceptibility mapping using Machine Learning and GIS: A case study of Kelantan by Azizan, Nur Afiqah

    Published 2020
    “…Then, the data of causative factor from the ArcGIS was being used in training in machine learning (ML). …”
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    Final Year Project
  17. 17

    Ultra-short-term PV power forecasting based on a support vector machine with improved dragonfly algorithm by Kishore, D. J. Krishna, Mohamed, M. R., Sudhakar, K., Jewaliddin, S. K., Peddakapu, K., Srinivasarao, P.

    Published 2021
    “…The proposed model of support vector machine (SVM) with improved dragonfly algorithm(IDA) is used to forecast the PV power. …”
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    Conference or Workshop Item
  18. 18

    Breast Cancer Prediction Model Using Machine Learning by Muhammad Amin, Bakri, Inna, Ekawati

    Published 2021
    “…Modelling with machine learning is done by selecting three candidate algorithms, namely Random Forest, Support Vector Machine, and Logistic Regression. …”
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    Article
  19. 19

    Binary Coati Optimization Algorithm- Multi- Kernel Least Square Support Vector Machine-Extreme Learning Machine Model (BCOA-MKLSSVM-ELM): A New Hybrid Machine Learning Model for Pr... by Sammen S.S., Ehteram M., Sheikh Khozani Z., Sidek L.M.

    Published 2024
    “…For water level prediction, lagged rainfall and water level are used. In this study, we used extreme learning machine (ELM)-multi-kernel least square support vector machine (ELM-MKLSSVM), extreme learning machine (ELM)-LSSVM-polynomial kernel function (PKF) (ELM-LSSVM-PKF), ELM-LSSVM-radial basis kernel function (RBF) (ELM-LSSVM-RBF), ELM-LSSVM-Linear Kernel function (LKF), ELM, and MKLSSVM models to predict water level. …”
    Article
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    Landslide risk zoning using support vector machine algorithm by Ghiasi V., Pauzi N.I.M., Karimi S., Yousefi M.

    Published 2024
    “…The weighted maps were then combined using the support vector machine algorithm. For the training and testing of the machine, 81 slippery ground points and 81 non-sliding points were used. …”
    Article