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    Clustering ensemble learning method based on incremental genetic algorithms by Ghaemi, Reza

    Published 2012
    “…In the first and second phases, a threshold fuzzy c-means clustering algorithm as a clusterer and a pattern ensemble learning method based on the incremental genetic-based algorithms are proposed respectively. …”
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    Thesis
  3. 3

    Pattern Classification of Human Epithelial Images by Mohd Isa, Mohd Fazlie

    Published 2016
    “…Last but not least, from the mean of properties, it will classify into the pattern after ranging the value of mean properties of each of the pattern itself that has been done in classification stage.…”
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    Final Year Project
  4. 4

    Analysis of K-Mean and X-Mean Clustering Algorithms Using Ontology-Based Dataset Filtering by Rahmah, Mokhtar, Raza, Muhammad Ahsan, Fauziah, Zainuddin, Nor Azhar, Ahmad, Raza, Muhammad Fahad, Raza, Binish

    Published 2021
    “…In this paper, we have compared the performance of K-Mean and XMean clustering algorithms using two datasets of student enrollment in higher education institutions. …”
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    Article
  5. 5

    HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC by Jamil, Nur Farahim

    Published 2014
    “…The algorithm gives a mean accuracy of 84% out of 125 test images.…”
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    Final Year Project
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    Bat algorithm for rough set attribute reduction by Taha A.M., Tang A.Y.C.

    Published 2023
    “…In this paper, a new optimization method has been introduced called bat algorithm for attribute reduction (BAAR), the proposed method is based mainly on the echolocation behavior of bats. …”
    Article
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    Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman by Che Osman, Siti Eshah

    Published 2019
    “…Due to the center biased nature of the videos, the HPSO algorithm uses an initial pattern (hexagon-shaped) to speed up the convergence of the algorithm. …”
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    Thesis
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    Autonomous anomaly detection using density-based features in streaming data / Muhammmad Yunus Iqbal Basheer by Iqbal Basheer, Muhammmad Yunus

    Published 2023
    “…Hence, it is critical for an anomaly detection algorithm to detect data anomalies patterns. Nonetheless, the process of detecting anomalies in streaming data is laborious. …”
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    Thesis
  9. 9

    Development of a new robust hybrid automata algorithm based on surface electromyography (SEMG) signal for instrumented wheelchair control by Mohd Hanafi, Muhammad Sidik

    Published 2020
    “…Addition of hybrid automata algorithm to run pattern and non-pattern recognition based control methods is an advantage to increase accuracy in differentiating forward stroke or hand return activity. …”
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    Thesis
  10. 10

    Optimized clustering with modified K-means algorithm by Alibuhtto, Mohamed Cassim

    Published 2021
    “…Besides, some real data sets were examined to validate the proposed algorithm. Empirical evidences based on simulated data sets indicated that the proposed modified k-means algorithm is able to recognise the optimum number of clusters for uncorrelated data sets. …”
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    Thesis
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    Customer segmentation on clustering algorithms by Toh, Wei Xuan

    Published 2023
    “…Firstly, descriptive analysis is performed to explore the characteristics of the dataset. Then, k-means, DBSCAN, and GMM clustering algorithms are applied to segment customers based on their buying behaviour. …”
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    Final Year Project / Dissertation / Thesis
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    A Comparative Study Of Fuzzy C-Means And K-Means Clustering Techniques by Sharifah Sakinah, Syed Ahmad

    Published 2014
    “…Clustering analysis has been considered as a useful means for identifying patterns in dataset. The aim for this paper is to propose a comparison study between two well-known clustering algorithms namely fuzzy c-means (FCM) and k-means. …”
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    Conference or Workshop Item
  13. 13

    Social media mining: a genetic based multiobjective clustering approach to topic modelling by Alfred, Rayner, Loo, Yew Jie, Obit, Joe Henry, Lim, Yuto, Haviluddin, Haviluddin, Azman, Azreen

    Published 2021
    “…Although effective, the performance of the k-means clustering algorithm depends heavily on the initial centroids and the number of clusters, k. …”
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    Article
  14. 14

    Flood Routing in River Reaches Using a Three-Parameter Muskingum Model Coupled with an Improved Bat Algorithm by Farzin, Saeed, Singh, Vijay, Karami, Hojat, Farahani, Nazanin, Ehteram, Mohammad, Kisi, Ozgur, Allawi, Mohammed Falah, Mohd, Nuruol Syuhadaa, El-Shafie, Ahmed

    Published 2018
    “…The results for the Wilson flood showed that the proposed model could reduce the Sum of Squared Deviations (SSD) value by 89%, 51%, 93%, 69%, and 88%, compared to the Genetic Algorithm (GA), Particle Swarm Optimization (PSO) algorithm, Pattern Search (PS) algorithm, Harmony Search (HS) algorithm, and Honey Bee Mating Optimization (HBMO), respectively. …”
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    Article
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    Pemahaman guru matematik Tahun Enam tentang pembahagian nombor bulat / Hoi Sim Min by Hoi , Sim Min

    Published 2018
    “…This study also found that teachers have four general patterns of thought and an algorithm to solve the problem of division of whole numbers, that is, the general pattern of thought of partition, measurement, repeated subtraction, the inverse of multiplication , and long division algorithm. …”
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    Thesis
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    A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition by Babiker, Elsadig Ahmed Mohamed

    Published 2002
    “…A vector quantization model that incorporate rough sets attribute reduction and rules generation with a modified version of the K-means clustering algorithm was developed, implemented and tested as a part of a speech recognition framework, in which the Learning Vector Quantization (LVQ) neural network model was used in the pattern matching stage. …”
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    Thesis
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    Biceps brachii surface EMG classification using neural networks by Chong, Yee Lin

    Published 2012
    “…In this module, statistical features such as mean, maximum, variance and standard deviation are computed to represent the signal pattern. …”
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    Thesis
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    Sistem Pengecaman Bentuk Berdasarkan FPGA by Zainal Ariffin, Nur Bayani

    Published 2005
    “…Pattern recognition means that the definition, identification and the classification by deciding the characteristics of that pattern which is need to be known. …”
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    Monograph
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    Mining Sequential Patterns using I-PrefixSpan by Saputra , Dhany, Dayang R.A. Rambli, Foong, Oi Mean

    Published 2008
    “…In this paper, we propose an improvement of pattern growth-based PrefixSpan algorithm, called I-PrefixSpan. …”
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    Citation Index Journal