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  1. 1
    Breast cancer disease classification using fuzzy-ID3 algorithm based on association function

    Breast cancer disease classification using fuzzy-ID3 algorithm based on association function by Nur Farahaina, Idris, Mohd Arfian, Ismail, Mohd Saberi, Mohamad, Shahreen, Kasim, Zalmiyah, Zakaria, Sutikno, Tole

    Published 2022
    “…The FID3-AF algorithm is a hybridisation of the fuzzy system, the iterative dichotomizer 3 (ID3) algorithm, and the association function. …”
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  2. 2
    Determining the preprocessing clustering algorithm in radial basis function neural network

    Determining the preprocessing clustering algorithm in radial basis function neural network by S.L. Ang, H.C. Ong, H.C. Law

    Published 2008
    “…Three types of method used in this study to find the centres include random selections, K-means clustering algorithm and also K-median clustering algorithm. …”
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  3. 3
    Training functional link neural network with ant lion optimizer

    Training functional link neural network with ant lion optimizer by Mohmad Hassim, Yana Mazwin, Ghazali, Rozaida

    Published 2020
    “…FLNN requires less tunable weights for training as compared to the standard multilayer feed forward network such as Multilayer Perceptron (MLP). Since FLNN uses Backpropagation algorithm as the standard learning algorithm, the method however prone to get trapped in local minima which affect its performance. …”
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  4. 4
    Functional link neural network with modified bee-firefly learning algorithm for classification task

    Functional link neural network with modified bee-firefly learning algorithm for classification task by Mohmad Hassim, Yana Mazwin

    Published 2016
    “…The standard learning method for tuning weights in FLNN is Backpropagation (BP) learning algorithm. …”
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  5. 5
    Arabic text classification using hybrid feature selection method using chi-square binary artificial bee colony algorithm

    Arabic text classification using hybrid feature selection method using chi-square binary artificial bee colony algorithm by Hijazi, Musab, Zeki, Akram M., Ismail, Amelia Ritahani

    Published 2021
    “…After that, the wrapper method, Artificial Bee Colony algorithm, is used as the second level where Naive Base is used as a fitness function. …”
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  6. 6
    Jogging activity recognition using k-NN algorithm

    Jogging activity recognition using k-NN algorithm by Afifah Ismail

    Published 2022
    “…The k-NN algorithm is a simple and easy-to-implement supervised machine learning algorithm that can be used to solve both classification and regression problems. …”
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    Academic Exercise
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  7. 7
    Fair bandwidth distribution marking and scheduling algorithm in network traffic classification

    Fair bandwidth distribution marking and scheduling algorithm in network traffic classification by Al-Kharasani, Ameen Mohammed Abdulkarem

    Published 2019
    “…Thus, proposing the method of reestimating the dropping functions in the RED algorithm. …”
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  8. 8
    Improving amphetamine-type stimulants drug classification using chaotic-based time-varying binary whale optimization algorithm

    Improving amphetamine-type stimulants drug classification using chaotic-based time-varying binary whale optimization algorithm by Draman @ Muda, Azah Kamilah, Mohd Yusof, Norfadzlia, Pratama, Satrya Fajri, Carbo-Dorca, Ramon, Abraham, Ajith

    Published 2022
    “…Firstly, a non-linear time-varying modified Sigmoid transfer function is used as the binarization method. Second, a hybrid Logistic-Tent chaotic map is employed to substitute the pseudorandom numbers of the probability operator in standard WOA. …”
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  9. 9
    An approach to improve functional link neural network training using modified artificial bee colony for classification task

    An approach to improve functional link neural network training using modified artificial bee colony for classification task by Mohmad Hassim, Yana Mazwin, Ghazali, Rozaida

    Published 2012
    “…The standard method for tuning the weight in FLNN is using a Backpropagation (BP) learning algorithm. …”
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  10. 10
    An approach to improve functional link neural network training using modified artificial bee colony for classification task

    An approach to improve functional link neural network training using modified artificial bee colony for classification task by Mohmad Hassim, Yana Mazwin, Ghazali, Rozaida

    Published 2012
    “…The standard method for tuning the weight in FLNN is using a Backpropagation (BP) learning algorithm. …”
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  11. 11
    Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm

    Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm by Dalatu, Paul Inuwa

    Published 2018
    “…We introduced two new approaches to normalization techniques to enhance the K-Means algorithms. …”
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  12. 12
    An approach to improve functional link neural network training using modified artificial bee colony for classification task

    An approach to improve functional link neural network training using modified artificial bee colony for classification task by Yana Mazwin Mohmad Hassim, Rozaida Ghazali

    Published 2013
    “…The standard method for tuning the weight in FLNN is using a Backpropagation (BP) learning algorithm. …”
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  13. 13
    Development of Hybrid Convolutional Neural Network and Radial Basis Function for Autism Spectrum Disorder Classification

    Development of Hybrid Convolutional Neural Network and Radial Basis Function for Autism Spectrum Disorder Classification by Huey Chern, Lim

    Published 2024
    “…Hence, this study proposed hybrid deep learning algorithms for ASD classification. Two algorithms merged: U-net neural network and Radial Basis Function (RBF) for medical image segmentation. …”
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  14. 14
    Image classification using two dimensional wavelet coefficients with parallel computing

    Image classification using two dimensional wavelet coefficients with parallel computing by Ong, Yew Fai

    Published 2020
    “…Furthermore, colour threshold analysis and edge detection algorithms are redesigned exclusively to refine the two-dimensional coefficients into a more meaningful low-level representation. …”
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  15. 15
    A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani

    A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani by Mahmoud Reza, Saybani

    Published 2016
    “…This thesis proposes three new hybrid algorithms: The FRA-AIRS2 algorithm uses fuzzy logic to improve data reduction capability of AIRS2 and to solve the linearity problem associated with resource allocation of AIRS. …”
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  16. 16
    Improved cuckoo search based neural network learning algorithms for data classification

    Improved cuckoo search based neural network learning algorithms for data classification by Abdullah, Abdullah

    Published 2014
    “…Artificial Neural Networks (ANN) techniques, mostly Back-Propagation Neural Network (BPNN) algorithm has been used as a tool for recognizing a mapping function among a known set of input and output examples. …”
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  17. 17
    Support directional shifting vector: A direction based machine learning classifier

    Support directional shifting vector: A direction based machine learning classifier by Kowsher, Md., Hossen, Imran, Tahabilder, Anik, Prottasha, Nusrat Jahan, Habib, Kaiser, Zafril Rizal, M Azmi

    Published 2021
    “…The positional error of the linear function has been modelled as a loss function which is iteratively optimized using the gradient descent algorithm. …”
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  18. 18
    Mutable Composite Firefly Algorithm for Microarray-Based Cancer Classification

    Mutable Composite Firefly Algorithm for Microarray-Based Cancer Classification by Fajila, Fathima, Yusof, Yuhanis

    Published 2024
    “…The proposed algorithm, named the CFS-Mutable Composite Firefly Algorithm (CFS-MCFA), is evaluated based on two metrics, namely classification accuracy and genes subset size, using a Support Vector Machine (SVM) classifier. …”
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  19. 19
    Modified anfis architecture with less computational complexities for classification problems

    Modified anfis architecture with less computational complexities for classification problems by Talpur, Noureen

    Published 2018
    “…Furthermore, researchers have mainly used metaheuristic algorithms to avoid the problem of local minima in standard learning method. …”
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  20. 20
    An improved algorithm for iris classification by using support vector machine and binary random machine learning

    An improved algorithm for iris classification by using support vector machine and binary random machine learning by Kamarulzalis, Ahmad Haadzal

    Published 2018
    “…The second objective is to conduct a supervised and binary ensemble machine learning technique for classification. This is done by using method of RF and RNN that share the same ensemble concept. …”
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