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  1. 1
    Reliability fuzzy clustering algorithm for wellness of elderly people

    Reliability fuzzy clustering algorithm for wellness of elderly people by N. J., Mohd Jamal, Ku Muhammad Naim, Ku Khalif, Mohd Sham, Mohamad

    Published 2019
    “…Fuzzy clustering is one of the unsupervised machine learning techniques based knowledge of data analysis that automated or semi-automated analytical model building. …”
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  2. 2
    Data mining in network traffic using fuzzy clustering

    Data mining in network traffic using fuzzy clustering by Mohamad, Shamsul

    Published 2003
    “…The production of clustering are used to build rules.…”
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  3. 3
    Data mining in network traffic using fuzzy clustering

    Data mining in network traffic using fuzzy clustering by Mohamad, Shamsul

    Published 2003
    “…The production of clustering are used to build rules.…”
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  4. 4
    A maximal-clique-based clustering approach for multi-observer multi-view data by using k-nearest neighbor with S-pseudo-ultrametric induced by a fuzzy similarity

    A maximal-clique-based clustering approach for multi-observer multi-view data by using k-nearest neighbor with S-pseudo-ultrametric induced by a fuzzy similarity by Khameneh, Azadeh Zahedi, Ghaznavi, Mehrdad, Kilicman, Adem, Mahad, Zahari, Mardani, Abbas

    Published 2024
    “…The proposed clustering algorithm is programmed and tested on synthetic and four real-world datasets using the R software. …”
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  5. 5
    An enhanced binary bat and Markov clustering algorithms to improve event detection for heterogeneous news text documents

    An enhanced binary bat and Markov clustering algorithms to improve event detection for heterogeneous news text documents by Al-Dyani, Wafa Zubair Abdullah

    Published 2022
    “…This work focuses on the FS problem by automatically detecting events through a novel wrapper FS method based on Adapted Binary Bat Algorithm (ABBA) and Adapted Markov Clustering Algorithm (AMCL), termed ABBA-AMCL. …”
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  6. 6
    Enhancement of Ant System Algorithm for Course Timetabling Problem

    Enhancement of Ant System Algorithm for Course Timetabling Problem by Djamarus, Djasli

    Published 2009
    “…This research starts with developing an algorithm based on original concept of Ant System Algorithm. …”
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  7. 7
    The implications for ahybrid detection technique against malicious sqlattacks on web applications

    The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

    Published 2025
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  8. 8
    Application Of Neural Network In Malaria Parasites Classification

    Application Of Neural Network In Malaria Parasites Classification by Lim, Chia Li

    Published 2006
    “…Multilayer Perceptron (MLP) network and Radial Basis Function (RBF) network will be developed using MATLAB in which MLP network is trained with Back Propagation, Bayesian Rule and Levenberg-Marquardt learning algorithm and RBF network is trained with k-means clustering algorithm. …”
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  9. 9
    Hardware Design Of Random Number Generator And Random Walk-Onboundary Algorithm To Compute Unit Cube Capacitance In Fpga

    Hardware Design Of Random Number Generator And Random Walk-Onboundary Algorithm To Compute Unit Cube Capacitance In Fpga by Niun, Cheah How

    Published 2016
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  10. 10
    Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method

    Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

    Published 2024
    thesis::doctoral thesis
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  11. 11
    Position-based multicast routing in mobile ad hoc networks: an analytical study

    Position-based multicast routing in mobile ad hoc networks: an analytical study by Qabajeh, Mohammad M., Hassan Abdalla Hashim, Aisha, Khalifa, Othman Omran, Qabajeh, Liana K.

    Published 2012
    “…The results show that the used virtual clustering is very useful in improving scalability and outperforms other clustering schemes. …”
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  12. 12
    Development of mesoscopic imaging system for surface inspection / Moe Win

    Development of mesoscopic imaging system for surface inspection / Moe Win by Moe , Win

    Published 2018
    “…Existing thresholding-based and clustering-based methods are tested and compared to achieve faster and more efficient algorithms. …”
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  13. 13
    Defect Detection And Classification Of Silicon Solar Wafer Featuring Nir Imaging And Improved Niblack Segmentation

    Defect Detection And Classification Of Silicon Solar Wafer Featuring Nir Imaging And Improved Niblack Segmentation by Mahdavipour, Zeinab

    Published 2016
    “…The classification combines the analysis of defect intensity features, the application of unsupervised k-mean clustering and multi-class SVM algorithms. The methods have been applied for detecting, clustering and classification polycrystalline solar wafer images, corresponding to defects such as micro cracks, stain, and fingerprints. …”
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  14. 14
    Small Dataset Learning In Prediction Model Using Box-Whisker Data Transformation

    Small Dataset Learning In Prediction Model Using Box-Whisker Data Transformation by Lateh, Masitah bdul

    Published 2020
    “…To test the effectiveness of the proposed algorithm, the real and generated samples is added to training phase to build a prediction model using M5 Model Tree. …”
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  15. 15
    Classification and prediction analysis for weld bead surface quality using feature extraction and mahalanobis-taguchi system

    Classification and prediction analysis for weld bead surface quality using feature extraction and mahalanobis-taguchi system by Nolia, Harudin, Muhammad Ikmal Hafiz, Mohd Yusof, Zulkifli, Marlah@Marlan, Faizir, Ramlie, Wan Zuki Azman, Wan Muhamad, Mohd Yazid, Abu, Zamzuraida, Baharum

    Published 2025
    “…This research develops an innovative algorithmic scoring system designed for the accurate assessment of welding bead samples in UNITEN’s welding laboratory. …”
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  16. 16
    An improved machine learning model of massive Floating Car Data (FCD) based on Fuzzy-MDL and LSTM-C for traffic speed estimation and prediction

    An improved machine learning model of massive Floating Car Data (FCD) based on Fuzzy-MDL and LSTM-C for traffic speed estimation and prediction by Ahanin, Fatemeh

    Published 2023
    “…In the second method, a new traffic estimation method is proposed using Fuzzy C-Mean (FCM) clustering and Minimum Description Length (MDL). MDL uses patterns to express the repeated presence in the data of particular items or clusters. …”
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  17. 17
    Content-based indexing of low resolution documents

    Content-based indexing of low resolution documents by Md Nor, Danial

    Published 2016
    “…We present hierarchy indexing techniques, whose foundation are tree and clustering. K-means clustering are used for visual features like colour since their spatial distribution give a good image’s global information. …”
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  18. 18
    Fruity vegetable recognition system using Color Histogram and BRISK features extraction / Siti Hajar Mohd Nasri

    Fruity vegetable recognition system using Color Histogram and BRISK features extraction / Siti Hajar Mohd Nasri by Mohd Nasri, Siti Hajar

    Published 2016
    “…In process to extract the two main features, K-means clustering algorithm is used as background subtraction method with combination of Canny’s Edge Detection and Mathematical Morphology Operation for shape extraction. …”
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  19. 19
    Understanding the occurrence of metastatic breast cancer through clinical, phenotype and genotype data, and the employment of machine learning / Nadia Jalaludin

    Understanding the occurrence of metastatic breast cancer through clinical, phenotype and genotype data, and the employment of machine learning / Nadia Jalaludin by Jalaludin, Nadia

    Published 2023
    “…The odds ratio of mutated gene, disease similarities and hierarchical clustering were also done before all the result was consolidated. …”
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  20. 20
    An enhanced synthetic oversampling framework with self-supervised contrastive learning for multi-class image imbalance

    An enhanced synthetic oversampling framework with self-supervised contrastive learning for multi-class image imbalance by Xiaoling, Gao

    Published 2025
    “…The second contribution is the introduction of the Clustering and Nearest Centroid Neighbour-based Synthetic Minority Oversampling (CLNCN-SMOTE) algorithm to resolve multi-class imbalance. …”
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