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  1. 1

    Improved whale optimization algorithm for feature selection in Arabic sentiment analysis by Tubishat, Mohammad, Abushariah, Mohammad A.M., Idris, Norisma, Aljarah, Ibrahim

    Published 2019
    “…In SA, feature selection phase is an important phase for machine learning classifiers specifically when the datasets used in training is huge. Whale Optimization Algorithm (WOA) is one of the recent metaheuristic optimization algorithm that mimics the whale hunting mechanism. …”
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    Article
  2. 2

    Time series predictive analysis based on hybridization of meta-heuristic algorithms by Mustaffa, Zuriani, Sulaiman, Mohd Herwan, Rohidin, Dede, Ernawan, Ferda, Kasim, Shahreen

    Published 2018
    “…The identified meta-heuristic methods namely Moth-flame Optimization (MFO), Cuckoo Search algorithm (CSA), Artificial Bee Colony (ABC), Firefly Algorithm (FA) and Differential Evolution (DE) are individually hybridized with a well-known machine learning technique namely Least Squares Support Vector Machines (LS-SVM). …”
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  3. 3

    Classification with degree of importance of attributes for stock market data mining by Khokhar, Rashid Hafeez, Md. Sap, Mohd. Noor

    Published 2004
    “…Alan Fan et aI., [2] use Support Vector Machine (SVM) to stock market prediction. The SVM is a training algorithm for learning classification and regression rules from data [7]. …”
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    Article
  4. 4

    Time series predictive analysis based on hybridization of meta-heuristic algorithms by Zuriani, Mustaffa, M. H., Sulaiman, Rohidin, Dede, Ernawan, Ferda, Shahreen, Kasim

    Published 2018
    “…The identified meta-heuristic methods namely Moth-flame Optimization (MFO), Cuckoo Search algorithm (CSA), Artificial Bee Colony (ABC), Firefly Algorithm (FA) and Differential Evolution (DE) are individually hybridized with a well-known machine learning technique namely Least Squares Support Vector Machines (LS-SVM). …”
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    Article
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    Stock market turning points rule-based prediction / Lersak Photong … [et al.] by Photong, Lersak, Sukprasert, Anupong, Boonlua, Sutana, Ampant, Pravi

    Published 2021
    “…Finally, rule-based optimisation techniques such as Particle Swarm Optimization (PSO), Differential Evolution (DE) and Grey Wolf Optimizer (GWO) were used to minimise the amount of time employed in the stock market turning points prediction. …”
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    Book Section
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    Design of smart waste bin and prediction algorithm for waste management in household area by Yusoff, Siti Hajar, Abdullah Din, Ummi Nur Kamilah, Mansor, Hasmah, Midi, Nur Shahida, Zaini, Syasya Azra

    Published 2018
    “…This study uses the information obtained from the smart waste bin for the waste weight while the sample size of KOE has been obtained through KOE’s department. …”
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    Article
  10. 10

    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
    “…In conclusion, the work demonstrates a novel method for using machine learning algorithms to classify, identify, and predict the contamination level of leftover cooked food, contributing to reducing food waste generated primarily by Malaysians…”
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    Article
  11. 11

    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
    “…Machine learning has emerged as a potential solution for plastic waste due to its ability to analyse and interpret large volumes of data using algorithms. …”
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    Article
  12. 12

    Computer algorithm for automated detection of intramedullary rod hole position and orientation / Ahmad Zulhilmi Mohd Ziyadi by Mohd Ziyadi, Ahmad Zulhilmi

    Published 2014
    “…It is achieve by using special algorithm that detect holes 2D coordinates and average width of intramedullary rod. …”
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    Thesis
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    Fault detection and diagnosis for gas density monitoring using multivariate statistical process control by Norul Shahida, Che Din, Noor Asma Fazli, Abdul Samad, Chin, Sim Yee

    Published 2011
    “…Therefore, an efficient fault detection and diagnosis algorithm needs to be developed to detect faults that are present in a process and pinpoint the cause of these detected faults. …”
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    Article
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    PCB defect detection system using run-length encoding by Zakaria, Muhammad Anif

    Published 2017
    “…Nowadays, electronic devices were widely used for the development of the technology. In PCB manufacturing many defects have been detected. …”
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    Student Project
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    An approach of classifying waste using transfer learning method by Amin, Zian Md Afique, Khan, Nasik Sami, Hassan, Raini

    Published 2021
    “…We will use dockers or Kubernetes to deploy and YOLO real-time object detection as a framework for the post.…”
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    Diabetic retinopathy pathological signs detection using image enhancement technique and deep learning / Abdul Hafiz Abu Samah …[et al.] by Abu Samah, Abdul Hafiz, Ahmad, Fadzil, Osman, Muhammad Khusairi, Md Tahir, Noritawati, Idris, Mohaiyedin, Abd. Aziz, Nor Azimah

    Published 2021
    “…Therefore, it is time-wasting and risky for humans to make mistake. In general, this paper introduces an automated machine learning algorithm for detecting diabetic retinopathy (DR) in fundus images. …”
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    Article
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    Evaluating endpoint detection algorithms for isolated word from Malay parliamentary speech by Seman N., Bakar Z.A., Bakar N.A., Mohamed H.F., Abdullah N.A.S., Ramakrisnan P., Ahmad S.M.S.

    Published 2023
    “…This paper presents the endpoint detection approaches specifically for an isolated word uses Malay spoken speeches from Malaysian Parliamentary session. …”
    Conference paper
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    Snort-based smart and swift intrusion detection system by Olanrewaju, Rashidah Funke, Khan, Burhan Ul Islam, Najeeb, Athaur Rahman, Ku zahir, Ku Nor Afiza, Hussain, Sabahat

    Published 2018
    “…Methods/Statistical Analysis: The features are extracted using back-propagation algorithm. Then, only these relevant features are trained with the help of multi-layer perceptron supervised neural network. …”
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    Article