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  1. 1
    Improved normalization and standardization techniques for higher purity in K-means clustering

    Improved normalization and standardization techniques for higher purity in K-means clustering by Dalatu, Paul Inuwa, Fitrianto, Anwar, Mustapha, Aida

    Published 2016
    “…Based on its simplicity, the K-means algorithm has been used in many fields. This paper proposes improved normalization and standardization techniques for higher purity in K-means clustering experimented with benchmark datasets from UCI machine learning repository and it was found that all the proposed techniques’ performance was much higher compared to the conventional K-means and the three classic transformations, and it is evidently shown by purity and Rand index accuracy results.…”
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  2. 2
    Ant colony optimization algorithm for load balancing in grid computing

    Ant colony optimization algorithm for load balancing in grid computing by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

    Published 2012
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  3. 3
    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing

    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

    Published 2011
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  4. 4
    Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly

    Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

    Published 2019
    “…This project will use fuzzy k-means clustering algorithm to cluster the data because it is easy to implement and have many advantages. …”
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  5. 5
    Resource management in grid computing using ant colony optimization

    Resource management in grid computing using ant colony optimization by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

    Published 2011
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  6. 6
    Dynamic force-directed graph with weighted nodes for scholar network visualization

    Dynamic force-directed graph with weighted nodes for scholar network visualization by Mohd. Aris, Khalid Al-Walid, Ramasamy, Chitra, Mohd Aris, Teh Noranis, Zolkepli, Maslina

    Published 2022
    “…The approach is realized by creating a web-based interface using D3 JavaScript algorithm that allows the visualization to focus on how data are connected to each other more accurately than the conventional lines of data seen in traditional data representation. …”
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  7. 7
    Comparing means of two non-homogeneous normal populations

    Comparing means of two non-homogeneous normal populations by Abd Rahman, Mohd Nawi

    Published 1986
    “…However, it can be attractive to many if some efficient algorithm is available. This paper intends to give an alternative approach for testing the means of two normal populations having unequal variances but whose coefficient of variations are homogeneous. …”
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  8. 8
    Integrating genetic algorithms and fuzzy c-means for anomaly detection

    Integrating genetic algorithms and fuzzy c-means for anomaly detection by Chimphlee, Witcha, Abdullah, Abdul Hanan, Sap, Noor Md., Chimphlee, Siriporn, Srinoy, Surat

    Published 2005
    “…Traditional anomaly detection algorithms require a set of purely normal data from which they train their model. …”
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  9. 9
    Widely linear dynamic quaternion valued least mean square algorithm for linear filtering

    Widely linear dynamic quaternion valued least mean square algorithm for linear filtering by Mohammed, Aldulaimi Haydar Imad

    Published 2017
    “…The new adaptive algorithm is called dynamic quaternion least mean square algorithm (DQLMS) because of the normalization process of the filter input and the variable step-size. …”
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  10. 10
    New approaches to normalization techniques to enhance k-means clustering algorithm

    New approaches to normalization techniques to enhance k-means clustering algorithm by Dalatu, Paul Inuwa, Midi, Habshah

    Published 2020
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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
    Short term forecasting based on hybrid least squares support vector machines

    Short term forecasting based on hybrid least squares support vector machines by Zuriani, Mustaffa, M. H., Sulaiman, Ernawan, Ferda, Noorhuzaimi, Mohd Noor

    Published 2018
    “…This study assesses the performance of each hybrid algorithms based on three statistical indices viz. Mean Square Error (MSE), Root Mean Square Percentage Error (RMSPE) and Theil’s U which is realized on raw and normalized data set. …”
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  13. 13
    Autonomous anomaly detection using density-based features in streaming data / Muhammmad Yunus Iqbal Basheer

    Autonomous anomaly detection using density-based features in streaming data / Muhammmad Yunus Iqbal Basheer by Iqbal Basheer, Muhammmad Yunus

    Published 2023
    “…Consequently, to handle these data, computer algorithms must adapt to their characteristics. …”
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  14. 14
    Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares

    Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares by Uraibi, Hassan Sami

    Published 2009
    “…One of the important assumptions of the linear model is that the error terms are normally distributed. Unfortunately, many researchers are not aware that the performance of the OLS can be very poor when the data set that one often makes a normal assumption, has a heavy-tailed distribution which may arise as a result of the presence of outliers. …”
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  15. 15
    A Comparative Study of Z-Score and Min-Max Normalization for Rainfall Classification in Pekanbaru

    A Comparative Study of Z-Score and Min-Max Normalization for Rainfall Classification in Pekanbaru by Rahmad Ramadhan, Laska, Anne Mudya, Yolanda

    Published 2024
    “…The objective is to compare various data normalization techniques, including Min-Max Normalization and Z-Score Normalization. …”
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  16. 16
    The normalized random map of gradient for generating multifocus image fusion

    The normalized random map of gradient for generating multifocus image fusion by Ismail, ., Kamarul Hawari, Ghazali

    Published 2020
    “…The proposed algorithm successes to supersede difficulties of mathematical equations and algorithms. …”
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  17. 17
    Reduced rank technique for joint channel estimation and joint data detection in TD-SCDMA systems

    Reduced rank technique for joint channel estimation and joint data detection in TD-SCDMA systems by Marzook, Ali Kamil, Ismail, Alyani, Mohd Ali, Borhanuddin, Sali, Aduwati, Khalaf, Mohannad H., Khatun, Sabira

    Published 2013
    “…The detectors: zero forcing block linear equalizer and minimum mean square error block linear equalizer algorithms are considered in this paper to recover the data. …”
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  18. 18
    The new efficient and accurate attribute-oriented clustering algorithms for categorical data

    The new efficient and accurate attribute-oriented clustering algorithms for categorical data by Qin, Hongwu

    Published 2012
    “…This work firstly reveals the significance of attributes in categorical data clustering, and then investigates the limitations of algorithms MMR and G-ANMI respectively, and correspondingly proposes a new attribute-oriented hierarchical divisive clustering algorithm termed Mean Gain Ratio (MGR) and an improved genetic clustering algorithm termed Improved G-ANMI (IG-ANMI) for categorical data. …”
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  19. 19
    Reduced Rank Technique for Joint Channel Estimation and Joint Data Detection in TD-SCDMA Systems

    Reduced Rank Technique for Joint Channel Estimation and Joint Data Detection in TD-SCDMA Systems by Sabira, Khatun, Ali K., Marzook, Alyani, Ismail, Aduwati, Sali, Mohannad Hamed, Khalaf, Borhan, M. Ali

    Published 2012
    “…The detectors: zero forcing block linear equalizer and minimum mean square error block linear equalizer algorithms are considered in this paper to recover the data. …”
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  20. 20
    Reduced-rank technique for joint channel estimation in TD-SCDMA systems.

    Reduced-rank technique for joint channel estimation in TD-SCDMA systems. by Ismail, Alyani, Sali, Aduwati, Mohd Ali, Borhanuddin, Khatun, Sabira

    Published 2013
    “…The detectors: zero forcing block linear equalizer and minimum mean square error block linear equalizer algorithms are considered in this paper to recover the data. …”
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