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  1. 1

    Bat Algorithm Based Hybrid Filter-Wrapper Approach by Taha A.M., Chen S.-D., Mustapha A.

    Published 2023
    “…This paper presents a new hybrid of Bat Algorithm (BA) based on Mutual Information (MI) and Naive Bayes called BAMI. …”
    Article
  2. 2

    A Bat-inspired Strategy for Pairwise Testing by Alsariera, Yazan A., Mazlina, Abdul Majid, Kamal Z., Zamli

    Published 2015
    “…Complementing the existing work, we propose a novel design and implementation of Bat-inspired algorithm (BA) for pairwise strategy, called Bat-inspired pairwise testing strategy (BPTS). …”
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  3. 3

    A bat-inspired testing strategy for generating constraints pairwise test suite by Alsariera, Yazan A., Ahmed, Hussam Alddin Shihab, Alamri, Hammoudeh S., Mazlina, Abdul Majid, Kamal Z., Zamli

    Published 2018
    “…This paper proposes an enhancement design and implementation of BTS strategy for constraints pairwise test generation based on the bat-inspired algorithm (BA). The benchmarking results of BTS show that it outperforms the generated test suite of the existing tools and strategies even in the presence of constraints.…”
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    Article
  4. 4

    A Bat-inspired Strategy for T-Way Interaction Testing by Kamal Z., Zamli, Alsariera, Yazan A.

    Published 2015
    “…As part of the strategy implementation, researchers have started to turn into meta-heuristic algorithms in line with the emergence of the new field called Search based Software Engineering. …”
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    Article
  5. 5

    FEATURES EXTRACTION OF FINGERPRINTS BASED ON HYBRID PARTICLE SWARM OPTIMIZATION AND BAT ALGORITHMS by Ahmed A.L., Hassoon N., Hak L.A.L., Edan M., Abed H., Abd S.

    Published 2023
    “…Both PSO and BA algorithms are swarmbased algorithms that mimics the swarm behaviour of particles and bats in nature. …”
    Article
  6. 6

    A class skew-insensitive ACO-based decision tree algorithm for imbalanced data sets by Mohd Razali, Muhamad Hasbullah, Saian, Rizauddin, Yap, Bee Wah, Ku-Mahamud, Ku Ruhana

    Published 2021
    “…This condition impeded the entropy-based heuristic of existing ATM algorithm to develop effective decision boundaries due to its biasness towards the dominant class. …”
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  7. 7

    Benchmarking of Bat-inspired Interaction Testing Strategy by Kamal Z., Zamli, Alsariera, Yazan A., Nasser, Abdullah B.

    Published 2016
    “…Recently, there are growing interests for adopting optimization algorithms as the basis of the newly developed strategies contributing to the new and upcoming search based software testing (SBST) area of research. …”
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    Article
  8. 8

    Identification model for hearing loss symptoms using machine learning techniques by Nasiru Garba Noma

    Published 2014
    “…In order to find, the correlation that exist between the hearing thresholds and symptoms of hearing loss, FP-Growth and association rule algorithms were first used to experiment with a small sample and large sample datasets. …”
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    Thesis
  9. 9

    Mobile app of mood prediction based on menstrual cycle using machine learning algorithm / Nur Hazirah Amir by Amir, Nur Hazirah

    Published 2019
    “…It implemented Supervised Learning algorithm with Bayes’ Theorem model for the calculation of mood prediction using Python programming language. …”
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    Thesis
  10. 10

    A bat-inspired t-way strategy for mixed-strength test suite generation by Ahmad, Yazan Sadeq Al Sariera

    Published 2017
    “…BTS is the first t-way strategy that adopts the Bat-inspired algorithm as its core implementation and adopts the Hamming distance as the final selection criteria to enhance the exploration of new solution. …”
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    Thesis
  11. 11

    Transfer learning in near infrared spectroscopy for stingless bee honey quality prediction across different months by Suarin, Nur Aisyah Syafinaz, Chia, Kim Seng, Mohamad Fuzi, Siti Fatimah Zaharah

    Published 2024
    “…Since it is unrealistic to have a NIRS dataset that can represent unforeseen future changes, an algorithm that can adapt existing data for new samples is worth to be investigated. …”
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    Article
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    Natural extensions: Bat algorithm with memory by Taha A.M., Chen S.-D., Mustapha A.

    Published 2023
    “…Bat Algorithm (BA) has recently started to attract a lot of attention as a powerful search method in various machine learning tasks including feature selection. …”
    Article
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    Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm by Reza M.S., Hannan M.A., Mansor M., Ker P.J., Rahman S.A., Jang G., Mahlia T.M.I.

    Published 2025
    “…In addition, to validate the prediction performance of the proposed LSA + LSTM model, extensive comparisons are performed with other popular optimization-based deep learning methods including artificial bee colony (ABC) based LSTM (ABC + LSTM), gravitational search algorithm (GSA) based LSTM (GSA + LSTM), and particle swarm optimization (PSO) based LSTM (PSO + LSTM) model using different error matrices. …”
    Article
  16. 16

    Color Image Segmentation Based on Bayesian Theorem for Mobile Robot Navigation by Rahimizadeh, Hamid

    Published 2009
    “…The experimental results show the proposed algorithm is simple and robust, for real time application on vision based mobile robot for navigation, in spite of presence of other shapes and colors in the environment …”
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    Thesis
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    Optimisation of Surface Roughness in 3D Printing Using the Bees Algorithm by Kamaruddin, Shafie, Ridzuan, Arman Hilmi, Sukindar, Nor Aiman

    Published 2025
    “…The result also shows that the Bees Algorithm found a better combination of parameters compared to other algorithms. …”
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    Book Chapter
  19. 19

    RFE-based feature selection to improve classification accuracy for morphometric analysis of craniodental characters of house rats by Aneesha Balachandran Pillay, Dharini Pathmanathan, Arpah Abu, Hasmahzaiti Omar

    Published 2023
    “…We also performed a comparative study based on three machine learning algorithms such as Naïve Bayes, Random Forest, and Artificial Neural Network by using all features and the RFE-selected features to classify the R. rattus sample based on the age groups. …”
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  20. 20

    Ganoderma boninense classification based on near-infrared spectral data using machine learning techniques by Mas Ira Syafila, Mohd Hilmi Tan, Mohd Faizal, Jamlos, Ahmad Fairuz, Omar, Kamarulzaman, Kamarudin, Mohd Aminudin, Jamlos

    Published 2022
    “…It is found the spectra of healthy samples are scattered on the negative sides of PC-1 while infected samples tend to be on a positive side with large loading coefficients marked significant discriminatory effect on healthy and infected samples at the wavelength of 1310 and 1452 nm. …”
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