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  1. 1
    Classification of Diabetes Mellitus (DM) using Machine Learning Algorithms

    Classification of Diabetes Mellitus (DM) using Machine Learning Algorithms by Sirajun Noor, Noor Azmiya

    Published 2021
    “…In this research, it was found that performance of ensemble method using hybrid classifier of Random Forest – Bayes Net model was found as the best DM classification model with an accuracy of 83.91% using the Pima Indian Diabetes Dataset (PIDD) out beating all the other classification algorithms. …”
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  2. 2
    Classification of Diabetes Mellitus using Ensemble Algorithms

    Classification of Diabetes Mellitus using Ensemble Algorithms by Noor, N.A.B.S., Elamvazuthi, I., Yahya, N.

    Published 2021
    “…The objective of this study is to perform DM classification using various machine learning algorithms. …”
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  3. 3
    Diabetes Diagnosis And Level Of Care Fuzzy Rule-Based Model Utilizing Supervised Machine Learning For Classification And Prediction

    Diabetes Diagnosis And Level Of Care Fuzzy Rule-Based Model Utilizing Supervised Machine Learning For Classification And Prediction by Mohd Aris, Teh Noranis, Abu Bakar, Azuraliza, Mahiddin, Normadiah, Zolkepli, Maslina

    Published 2024
    “…In addition, level of care dataset reveals the highest accuracy of 97.15% for MLP and Bagging algorithms and the lowest accuracy of 91.66% for stacking algorithm. …”
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  4. 4
    Urban landcover features identification utilizing multiband combinations and multi-level image segmentation for objectbased classification / Nurhanisah Hashim

    Urban landcover features identification utilizing multiband combinations and multi-level image segmentation for objectbased classification / Nurhanisah Hashim by Hashim, Nurhanisah

    Published 2018
    “…Twelve segmentation levels were constructed in order to create meaningful image objects before going through the classification process. …”
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  5. 5
    Data Mining Analysis Of Chronic Kidney Disease (CKD) Level

    Data Mining Analysis Of Chronic Kidney Disease (CKD) Level by Mohd Harizi, Muhammad Hafizam Afiq

    Published 2022
    “…The ZeroR algorithm was set as the baseline There are three levels of classification analyses: before and after handling the missing values, before and after the outliers’ treatment, and adding uncertain classes. …”
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  6. 6
    Leaf lesion classification (LLC) algorithm based on artificial bee colony (ABC)

    Leaf lesion classification (LLC) algorithm based on artificial bee colony (ABC) by Ahmad, Faudziah, Ku-Mahamud, Ku Ruhana, Sainin, Mohd Shamrie, Airuddin, Ahmad

    Published 2015
    “…Results showed that the Leaf Lesion Classification (LLC) algorithm based on Artificial Bee colony (ABC) produced an average 96.83% of accuracy and average 1.66 milliseconds of processing time, indicating that LLC algorithm is better than algorithm such as Otsu, Canny, Roberts and Sobel. …”
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  7. 7
    Evaluating Bees Algorithm for Sequence-based T-way Testing Test Data Generation

    Evaluating Bees Algorithm for Sequence-based T-way Testing Test Data Generation by M. H., Mohamed Zabil, Kamal Z., Zamli, K. C., Lim

    Published 2018
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  8. 8
    Texture-based feature using multi-blocks gray level co-occurrence matrix for ethnicity identification

    Texture-based feature using multi-blocks gray level co-occurrence matrix for ethnicity identification by Mohd Zamri, Osman, M. A., Maarof, Mohd Foad, Rohani

    Published 2020
    “…Then, final stage was undergone with several classification algorithms such as Naïve Bayes, BayesNet, kNearest Neighbour (k-NN), Random Forest, and Multilayer Perceptron (MLP). …”
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  9. 9
    Flowshop scheduling using artificial bee colony (ABC) algorithm with varying onlooker bees approaches

    Flowshop scheduling using artificial bee colony (ABC) algorithm with varying onlooker bees approaches by Mohd Pauzi, Nur Fazlinda

    Published 2015
    “…The performance of the ABC algorithm was evaluated through three different onlooker approaches i.e. method 3+0+0 (three onlooker bees are dedicated to the best employee bee), method 2+1+0 (two onlooker bees are dedicated to the best employee bee and one onlooker bee is dedicated to second best employee bee) and method 1+1+1 (one onlooker bee is dedicated to each employee bee). …”
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  10. 10
    An intra-severity classification and adaptation technique to improve dysarthric speech recognition accuracy / Bassam Ali Qasem Al-Qatab

    An intra-severity classification and adaptation technique to improve dysarthric speech recognition accuracy / Bassam Ali Qasem Al-Qatab by Bassam Ali Qasem, Al-Qatab

    Published 2020
    “…The algorithms include Linear Discriminant Analysis (LDA), Artificial Neural Network (ANN), Support Vector Machine (SVM), Naive Bayes (NB), Classification And Regression Tree (CART), Random Forest (RF). …”
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  11. 11
    Home buyer assistant using artificial bee colony algorithm / Muhammad Izzat Azri Azman

    Home buyer assistant using artificial bee colony algorithm / Muhammad Izzat Azri Azman by Azman, Muhammad Izzat Azri

    Published 2017
    “…This project used Artificial Bee Colony Algorithms (ABC) by adapting the food foraging behaviour of bee in honey bee and find a suitable house for home buyer based on their requirement. …”
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  12. 12
    An early warning detection system of terrorism in indonesia from Twitter contents using naïve bayes algorithm

    An early warning detection system of terrorism in indonesia from Twitter contents using naïve bayes algorithm by Aryuni, Mediana, Miranda, Eka, Fernando, Yudi, Kibtiah, Tia Mariatul

    Published 2020
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  13. 13
    Pixel-based feature for android malware family classification using machine learning algorithms

    Pixel-based feature for android malware family classification using machine learning algorithms by Mohd Zamri, Osman, Rahiwan Nazar, Romli, Ahmad Firdaus, Zainal Abidin, Mohd Faaizie, Darmawan

    Published 2021
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  14. 14
    Algorithm in the fluidized-bed reactor for the polymerization of propylene

    Algorithm in the fluidized-bed reactor for the polymerization of propylene by Zanil, Mohd Fauzi, Chan, K.O., Hussain, Mohd Azlan

    Published 2019
    “…A modified artificial bee optimization is proposed in this study. The algorithm is based on the colony behavior of certain bee species to achieve optimal solution in the bounded environment. …”
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  15. 15
    Prediction of college student academic performance using data mining techniques.

    Prediction of college student academic performance using data mining techniques. by Abd Jalil, Azura, Mustapha, Aida, Santa, Dzulizah, Zain, Nurul Zaiha, Radwan, Rizalina

    Published 2013
    “…This study attempts to predict the success rate of students’ academic performance by analyzing their examination results to secure a place at college level for the subsequent semester. The classification algorithms used are the Decision Tree, Naïve Bayesian, and Multilayer Perception with the highest classification accuracy by the Naive Bayes algorithm with accuracy of 95.3%. …”
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  16. 16
    Classification of basal stem rot disease in oil palm using dielectric spectroscopy

    Classification of basal stem rot disease in oil palm using dielectric spectroscopy by Al-Khaled, Al-Fadhl Yahya Khaled

    Published 2018
    “…Without implementing any data reduction algorithm, the highest classification accuracy was found in SVM classifier with 79.55%. …”
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  17. 17
    An efficient intrusion detection model based on hybridization of artificial bee colony and dragonfly algorithms for training multilayer perceptrons

    An efficient intrusion detection model based on hybridization of artificial bee colony and dragonfly algorithms for training multilayer perceptrons by Ghanem, Waheed Ali H. M., Aman, Jantan, Ahmed Ghaleb, Sanaa Abduljabbar, Naseer, Abdullah B.

    Published 2020
    “…This study proposes a new binary classification model for intrusion detection, based on hybridization of Artificial Bee Colony algorithm (ABC) and Dragonfly algorithm (DA) for training an artificial neural network (ANN) in order to increase the classification accuracy rate for malicious and non-malicious traffic in networks. …”
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  18. 18
    Classification of Cognitive Frailty in Elderly People from Blood Samples using Machine Learning

    Classification of Cognitive Frailty in Elderly People from Blood Samples using Machine Learning by Idris, S., Badruddin, N.

    Published 2021
    “…A total of 7 different classification algorithms were used to predict between 6 levels of CF, the Robust and Non-Robust groups, as well as the Robust and Frail with MCI groups. …”
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  19. 19
    Binary Artificial Bee Colony Optimization For Weighted Random 2 Satisfiability In Discrete Hopfield Neural Network

    Binary Artificial Bee Colony Optimization For Weighted Random 2 Satisfiability In Discrete Hopfield Neural Network by Muhammad Sidik, Siti Syatirah

    Published 2023
    “…Hence, this thesis will utilize Non-Systematic Weighted Random 2 Satisfiability incorporating with Binary Artificial Bee Colony algorithm in Discrete Hopfield Neural Network. …”
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  20. 20
    Multiobjective optimization using weighted sum Artificial Bee Colony algorithm for Load Frequency Control

    Multiobjective optimization using weighted sum Artificial Bee Colony algorithm for Load Frequency Control by Naidu, K., Mokhlis, Hazlie, Bakar, Ab Halim Abu

    Published 2014
    “…This paper presents the implementation of multiobjective based optimization of Artificial Bee Colony (ABC) algorithm for Load Frequency Control (LFC) on a two area interconnected reheat thermal power system. …”
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