Search Results - (((( pattern means algorithm ) OR ( pattern bees algorithm ))) OR ( between mining algorithm ))

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  1. 1

    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
  2. 2

    A modified π rough k-means algorithm for web page recommendation system by Zidane, Khaled Ali Othman

    Published 2018
    “…Hence, this study carried out several objectives to augment the support of modified clustering algorithm. Firstly, an extended K-Means clustering algorithm (called X-Means algorithm) is proposed to filter/remove the noise from user session data to eliminate outliers or irrelevant pages. …”
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    Thesis
  3. 3

    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
    “…Then, the mapping percentages between the predefined and produced clusters are used to assess the performance of the proposed algorithm. …”
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    Article
  4. 4

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

    Published 2021
    “…Then, the mapping percentages between the predefined and produced clusters are used to assess the performance of the proposed algorithm. …”
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    Article
  5. 5

    Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model by Sulaiman, Md. Nasir, Mohamed, Raihani, Mustapha, Norwati, Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…Clustering is one of the means in data mining of predicting the class based on separating the data categories from similar features. …”
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    Article
  6. 6

    Prediction of Rainfall Trends using Mahalanobis-Taguchi System by Jamil M.A.M., Abu M.Y., Zaini S.N.A.M., Aris N.H., Pinueh N.S., Jaafar N.N., Muhammad W.Z.A.W., Ramlie F., Harudin N., Sari E., Ghani N.A.A.A.

    Published 2025
    “…Finally, the validation with T mean-based error (Tmbe) using Mean Absolute Error (MAE) revealed a pattern of errors to provide insight to find the significant parameters of MTS. ? …”
    Article
  7. 7

    Optimization Of Pid Controller For Double-Link Flexible Robotic Manipulator Using Metaheuristic Algorithms by Annisa, Jamali, Intan Zaurah, Mat Darus, Hanim, Mohd Yatim, Mat Hussin, Ab Talib

    Published 2019
    “…This paper investigates the optimization approach of PID controller for double-link flexible robotic manipulator using metaheuristic algorithm. This research focus on population-based metaheuristic that is particle swarm optimization (PSO) and artificial bees algorithm (ABC) to tune the PID control parameters of the system. …”
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    Proceeding
  8. 8

    Prediction of rainfall trends using Mahalanobis-Taguchi system by Muhammad Arieffuddin, Mohd Jamil, Mohd Yazid, Abu, Sri Nur Areena, Mohd Zaini, Nurul Haziyani, Aris, Nur Syafikah, Pinueh, Nur Najmiyah, Jaafar, Wan Zuki Azman, Wan Muhammad, Faizir, Ramlie, Nolia, Harudin, Emelia Sari, ., Nadiatul Adilah, Ahmad Abdul Ghani

    Published 2024
    “…Finally, the validation with T mean-based error (Tmbe) using Mean Absolute Error (MAE) revealed a pattern of errors to provide insight to find the significant parameters of MTS.…”
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    Article
  9. 9

    Enhancement of text representation for Indonesian document summarization with deep sequential pattern mining by Dian Sa’adillah Maylawati

    Published 2023
    “…Therefore, the present study aims: (1) to improve Indonesian text summary by enhancing the Sequence of Word (SoW) as text representation using Sequential Pattern Mining (SPM) with PrefixSpan algorithm since the effectiveness of SPM in Indonesian is proven useful for text classification and clustering; (2) to combine SPM and Deep Learning (DeepSPM) in text summarization with Indonesian text, as a result of its superior accuracy when trained with large amounts of data; and (3) to evaluate the readability of Indonesian text summary with several evaluation scenarios. …”
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    Thesis
  10. 10

    Assessing data mining as an alternative in discovering customer consumption pattern / Abdul Malik Hafiy Mohd Jeffri, Muhammad Aqil Zulkifli and Sukri Nasruddin by Mohd Jeffri, Abdul Malik Hafiy, Zulkifli, Muhammad Aqil, Nasruddin, Sukri

    Published 2019
    “…Data were analysed by using Rstudio software and apriori algorithm is used for obtaining the pattern. The first objective is to generate the frequent item sets that are frequently bought by customers. …”
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    Student Project
  11. 11

    An analysis of text mining factors enhancing the identification of relevant studies by Khashfeh M., Mahmoud M.A., Ahmad M.S.

    Published 2023
    “…The second component is the search process that is operated by a pattern matching. The third process is the parsing that is operated by a text mining algorithm. …”
    Article
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    Neural Network Training Using Hybrid Particle-move Artificial Bee Colony Algorithm for Pattern Classification by Nuaimi, Zakaria Noor Aldeen Mahmood Al, Abdullah, Rosni

    Published 2017
    “…Artificial Bees Colony (ABC) optimization algorithm is one of the competitive algorithms in the SI algorithms group. …”
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    Article
  14. 14

    Neural network training using hybrid particle-move artificial bee colony algorithm for pattern classification by Al Nuaimi, Zakaria Noor Aldeen Mahmood, Abdullah, Rosni

    Published 2017
    “…In this work, we aimed to highlight the performance of the Hybrid Particle-move Artificial Bee Colony (HPABC) algorithm by applying it on the ANNT application.The performance of the HPABC algorithm was investigated on four benchmark pattern-classification data sets and the results were compared with other algorithms.The results obtained illustrate that HPABC algorithm can efficiently be used for ANNT.HPABC outperformed the original ABC and PSO as well as other state-of-art and hybrid algorithms in terms of time, function evaluation number and recognition accuracy.…”
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    Article
  15. 15

    Application of the bees algorithm to the selection features for manufacturing data by Pham, D.T, Mahmuddin, Massudi, Otri, S., Al-Jabbouli, H.

    Published 2007
    “…The Bees Algorithm is employed to select an optimal set of features for a particular pattern classification task. …”
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    Conference or Workshop Item
  16. 16

    Classification Of Gender Using Global Level Features In Fingerprint For Malaysian Population by Abdullah, Siti Fairuz

    Published 2016
    “…For the classification part, five extracted features of the fingerprint are used which are Ridge Density (RD), Mean Ridge Count (RC), Ridge Thickness to Valley Thickness Ratio (RTVTR), White Lines Count (WLC) and Mean Pattern Types (PT). …”
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    Thesis
  17. 17

    An automated learner for extracting new ontology relations by Amaal Saleh Hassan, Al Hashimy, Narayanan, Kulathuramaiyer

    Published 2013
    “…Also we present a novel approach of learning based on the best lexical patterns extracted, besides two new algorithms the CIA and PS that provide the final set of rules for mining causation to enrich ontologies.…”
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    Article
  18. 18

    A COMPARISON STUDY OF DATA CLUSTERING AND VISUALISATION TECHNIQUES WITH VARIOUS DATA TYPES by Ling, Chien

    Published 2020
    “…The clustering algorithms are written using Python language by modifying the coding obtained from the Internet. …”
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    Final Year Project Report / IMRAD
  19. 19

    Clustering natural language morphemes from EEG signals using the Artificial Bee Colony algorithm by Sulaiman, Suriani, Ahmed Yahya, Saba, Mohd Shukor, Nur Sakinah, Ismail , Amelia Ritahani, Zaahirah, Qazi, Yaacob, Hamwira, Abdul Rahman, Abdul Wahab, Dzulkifli, Mariam Adawiah

    Published 2015
    “…This study aims at analyzing EEG signals for the purpose of clustering natural language morphemes using the Artificial Bee Colony (ABC) algorithm. Using as input the features extracted from EEG signals during morphological priming tasks, our experimental results indicate that applying the ABC algorithm on EEG datasets to cluster Malay morphemes produces promising results.…”
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    Proceeding Paper
  20. 20

    Modifying iEclat algorithm for infrequent patterns mining by Julaily Aida, J., Mustafa, M.

    Published 2018
    “…This paper proposes an enhancement algorithm based on iEclat algorithms for mining infrequent pattern.…”
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    Conference or Workshop Item