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  1. 1

    A review of Artificial Intelligence application of sustainable solid waste management practices in Western Asia by Nagimeldin, Olla, Ahmad Tajuddin, Husna, Jami, Mohammed Saedi

    Published 2022
    “…Over the past few years, Machine-learning algorithms and Artificial intelligence models have demonstrated great ability to optimize and automate critical solid waste and waste management complications. …”
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    Proceeding Paper
  2. 2

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

    Published 2020
    “…So, we are proposing an automated waste classification problem utilizing Machine Learning and Deep Learning algorithms. …”
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    Article
  3. 3

    Automated density and growth estimation in precision aquaculture systems for prawn cultivation using computer vision techniques by Chong, Xiao Wei

    Published 2024
    “…To address these challenges, this project proposes an innovative solution that leverages computer vision and machine learning techniques. By employing the state-of-the-art You Only Look Once (YOLO) v7 object detection algorithm, the project aims to develop a system capable of accurately detecting and classifying prawns based on their growth stages. …”
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    Final Year Project / Dissertation / Thesis
  4. 4

    Evaluating different machine learning models for predicting municipal solid waste generation: a case study of Malaysia by Latif S.D., Hazrin N.A.B., Younes M.K., Ahmed A.N., Elshafie A.

    Published 2025
    “…Therefore, one of the aims of this research was to investigate the use of machine learning algorithms and its benefits. The machine learning algorithms investigated are specifically Gaussian process regression (GPR), ensemble of trees and neural networks. …”
    Article
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    An Embedded Machine Learning-Based Spoiled Leftover Food Detection Device for Multiclass Classification by Wan Azman,, Wan Nur Fadhlina Syamimi, Ku Azir, Ku Nurul Fazira, Mohd Khairuddin, Adam

    Published 2024
    “…This work proposes using machine learning algorithms and electronic nose technology to recognise and forecast the contamination in leftover cooked food. …”
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    Article
  7. 7

    RGB and RGNIR image dataset for machine learning in plastic waste detection by Owen Tamin, Ervin Gubin Moung, Jamal Ahmad Dargham, Samsul Ariffin Abdul Karim, Ashraf Osman Ibrahim Elsayed, Nada Adam, Hadia Abdelgader Osman

    Published 2025
    “…The proposed dataset offers a unique resource for researchers to train machine learning models for plastic waste detection. …”
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    Article
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    Classification model for water quality using machine learning techniques by Azilawati, Rozaimee, Azrul Amri, Jamal, Azwa, Abdul Aziz

    Published 2015
    “…This article proposes a suitable classification model for classifying water quality based on the machine learning algorithms. The paper analyzed and compared performance of various classification models and algorithms in order to identify the significant features that contributed in classifying water quality of Kinta River, Perak Malaysia. …”
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    Article
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    Using predictive analytics to solve a newsvendor problem / S. Sarifah Radiah Shariff and Hady Hud by Shariff, S. Sarifah Radiah, Hud, Hady

    Published 2023
    “…Secondly, in solving every Machine Learning problem, there is no one algorithm superior to other algorithms. …”
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    Book Section
  15. 15

    Performance analysis of support vector machine, Gaussian Process Regression, sequential quadratic programming algorithms in modeling hydrogen-rich syngas production from catalyzed... by Ayodele, B.V., Mustapa, S.I., Kanthasamy, R., Mohammad, N., AlTurki, A., Babu, T.S.

    Published 2022
    “…Taking advantage of the data generated from the process, this study explores the performance of twelve machine learning algorithms built on the support vector machine (SVM), the Gaussian process regression (GPR), and the non-linear response quadratic model (NLRQM) using Sequential quadratic programming, and the Levenberg-Marquardt algorithms. …”
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    Article
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    Performance analysis of support vector machine, Gaussian Process Regression, sequential quadratic programming algorithms in modeling hydrogen-rich syngas production from catalyzed... by Ayodele, B.V., Mustapa, S.I., Kanthasamy, R., Mohammad, N., AlTurki, A., Babu, T.S.

    Published 2022
    “…Taking advantage of the data generated from the process, this study explores the performance of twelve machine learning algorithms built on the support vector machine (SVM), the Gaussian process regression (GPR), and the non-linear response quadratic model (NLRQM) using Sequential quadratic programming, and the Levenberg-Marquardt algorithms. …”
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    Article
  19. 19

    Fault classification in transmission line using single layer feed-forward network trained by extreme learning machine / Muhamad Azfar Abd Ghafar by Abd Ghafar, Muhamad Azfar

    Published 2015
    “…The SLFN is trained by an algorithm named Extreme Learning Machine (ELM). The extracted features will be fed up into SLFN to classify the fault. …”
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    Thesis
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    Fault classification in transmission line using single layer feed-forward network trained by extreme learning machine / Muhamad Azfar Abd Ghafar by Abd Ghafar, Muhamad Azfar

    Published 2015
    “…The SLFN is trained by an algorithm named Extreme Learning Machine (ELM). The extracted features will be fed up into SLFN to classify the fault. …”
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    Student Project