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  1. 1

    Whale optimization algorithm based on tent chaotic map for feature selection in soft sensors by AlRijeb, Mothena Fakhri Shaker, Othman, Mohammad Lutfi, Ishak, Aris, Hassan, Mohd Khair, Albaker, Baraa Munqith

    Published 2025
    “…One of the powerful optimization algorithms that is used for feature selection is the Whale Optimization Algorithm (WOA), which is a nature-inspired metaheuristic optimization algorithm that mimics the social behavior of humpback whales. …”
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  2. 2

    Whale Optimisation Freeman Chain Code (WO-FCC) extraction algorithm for handwritten character recognition by Muhammad Arif, Mohamad, Jamaludin, Sallim, Kohbalan, Moorthy

    Published 2021
    “…In this paper, we propose a metaheuristic method for feature extraction algorithm with Whale Optimisation Algorithm (WOA) based HCR. …”
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  3. 3

    Binary whale optimization algorithm with logarithmic decreasing time-varying modified sigmoid transfer function for descriptor selection problem by Yusof, Norfadzlia Mohd, Muda, Azah Kamilah, Pratama, Satrya Fajri, Carbo-Dorca, Ramon, Abraham, Ajith

    Published 2023
    “…The new Binary Whale Optimization Algorithm is integrated with wrapper feature selection and validated on descriptor selection problem to improve Amphetamine-type stimulants drug classification result. …”
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  4. 4

    An improve unsupervised discretization using optimization algorithms for classification problems by Mohamed, Rozlini, Samsudin, Noor Azah

    Published 2024
    “…Recognizing the critical role of discretization in enhancing classification performance, the study integrates equal width binning (EWB) with two optimization algorithms: the bat algorithm (BA), referred to as EB, and the whale optimization algorithm (WOA), denoted as EW. …”
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  5. 5

    An improve unsupervised discretization using optimization algorithms for classification problems by Mohamed, Rozlini, Samsudin, Noor Azah

    Published 2024
    “…Recognizing the critical role of discretization in enhancing classification performance, the study integrates equal width binning (EWB) with two optimization algorithms: the bat algorithm (BA), referred to as EB, and the whale optimization algorithm (WOA), denoted as EW. …”
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  6. 6

    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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  7. 7

    Impact of Balanced Exploration and Exploitation on High-dimensional Feature Selection with Hierarchical Whale Optimisation Algorithm by Yab, Li Yu, Wahid, Noorhaniza, A Hamid, Rahayu

    Published 2024
    “…Hence, this study introduced the Hierarchical Whale Optimisation Algorithm (HiWOA), an approach designed to enhance the WOA’s stability and performance in HDD feature selection tasks. …”
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  8. 8

    Improved Ozone Level Detection through Feature Selection with Modified Whale Optimization Algorithm by Yab, Li Yu, Wahid, Noorhaniza, A. Hamid, Rahayu

    Published 2024
    “…This study presents a new approach for ozone level detection through feature selection by the modified Whale Optimization Algorithm (mWOA). …”
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  9. 9

    Improved Ozone Level Detection through Feature Selection with Modified Whale Optimization Algorithm by Li Yu Yab, Li Yu Yab, Wahid, Noorhaniza, A. Hamid, Rahayu

    Published 2024
    “…This study presents a new approach for ozone level detection through feature selection by the modified Whale Optimization Algorithm (mWOA). …”
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  10. 10

    Hybrid binary whale with harris hawks for feature selection by Alwajih, R., Abdulkadir, S.J., Al Hussian, H., Aziz, N., Al-Tashi, Q., Mirjalili, S., Alqushaibi, A.

    Published 2022
    “…When compared to existing algorithms, the proposed approach produced better results. …”
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  11. 11

    Unleashing the power of Manta Rays Foraging Optimizer: A novel approach for hyper-parameter optimization in skin cancer classification by Adamu, Shamsuddeen, Alhussian, Hitham, Aziz, Norshakirah, Abdulkadir, Said Jadid, Alwadin, Ayed, Abdullahi, Mujaheed, Garba, Aliyu

    Published 2025
    “…Empirical evaluations on diverse datasets (ISIC, PH2, HAM10000) showcase the significant superiority of the MRFO-based model over conventional optimization algorithms. The model achieves impressive accuracy and loss metrics (ISIC: 99.43 , 0.0250; PH2: 99.96 , 0.0033; HAM10000: 97.70 , 0.0626), outperforming alternative optimization algorithms such as the Grey Wolf Optimizer (98.33 accuracy, 0.17 loss), Whale Optimization Algorithm (96 accuracy), Grasshopper Optimization Algorithm (97.2 accuracy), Densnet121-MRFO (99.26 accuracy), InceptionV3 with GA (99.9 accuracy), and African Vulture Optimization Algorithm (92.7 accuracy). …”
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    Using algorithmic taxonomy to evaluate lecturer workload by Hashim, Ruhil Hayati, Abdul Hamid, Jamaliah, Selamat, Mohd Hasan, Ibrahim, Hamidah, Abdullah, Rusli, Mohayidin, Mohd Ghazali

    Published 2006
    “…Results of the study highlight the contributions of this algorithmic method in better evaluation of teaching workload for lecture.…”
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  14. 14

    Using algorithmic taxonomy to evaluate lecture workload: a case study of services application prototype in the UPM KM Portal by Abdul Hamid, Jamaliah, Mohayidin, Mohd Ghazali, Selamat, Mohd Hasan, Ibrahim, Hamidah, Abdullah, Rusli, Hashim, Ruhil Hayati

    Published 2006
    “…Results of the study highlight the contributions of this algorithmic method in better evaluation of teaching workload for lecture.…”
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  15. 15

    Using algorithmic taxonomy to evaluate lecture workload: A case study of services application prototype in the UPM KM portal by Abdul Hamid, Jamaliah, Mohayidin, Mohd Ghazali, Selamat, Mohd Hassan, Ibrahim, Hamidah, Abdullah, Rusli, Hashim, Ruhil Hayati

    Published 2006
    “…Lecturer workload at universities includes three major categories: teaching, research and services.Teaching workload is influence by various factors such as level taught courses, number of student, credit and contact hour and off campus or on campus course design.The UPM has a KM Portal that contains sets of metadata on lecturer profile and knowledge assets.The Lecturer profile contains information lecturer teaching, research, publication and many more.We constructed an algorithmic taxonomy based at the lecturer profile data to measure lecturer teaching workload.This method measures the lecturer teaching workload.The taxonomy is a dynamic hierarchy that extracts validated parameters from the dataset.Results of the study highlight the contributions of this algorithmic method in better evaluation of teaching workload for lecture.…”
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  16. 16

    Using web questionnaire for web-based course evaluation: advantages and disadvantages by Fariborzi, Elham, Abu Bakar, Kamariah, Kasa, Zakaria, Abu Samah, Bahaman, Abdullah, Muhammad Taufik

    Published 2017
    “…This article examines some advantages and disadvantages of conducting Web survey research especially for Web-based course evaluation at Iranian university E-learning centers. …”
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    Graph theory approach for managing lecturers’ schedule using graph colouring method / Siti Nor Ba Basri, Nur Su’aidah Khozaid and Farhana Hazwani Ismail by Basri, Siti Nor Ba, Khozaid, Nur Su’aidah, Ismail, Farhana Hazwani

    Published 2023
    “…In this study, the scheduling problem is represented as a graph where vertices represent time slots and edges represent conflicts or dependencies between courses and lecturers. Different colours are allocated to each vertex using graph colouring techniques such as the vertices algorithm or the edges algorithm, ensuring that clashing courses and lecturers are assigned different time slots. …”
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    Student Project
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    Information fusion and data augmentation with deep features for a deep learning-based baby cry recognition / Zhang Ke by Zhang , Ke

    Published 2024
    “…To validate the effectiveness of the proposed method, examples are analyzed, and applied in baby cry recognition. The Whale optimization algorithm-Variational mode decomposition is used to optimally decompose the baby cry signals. …”
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    Thesis