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  1. 1

    Route Optimization System by Zulkifli, Abdul Hayy

    Published 2005
    “…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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    Final Year Project
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    Fuzzy modeling using Bat Algorithm optimization for classification by Noor Amidah, Ahmad Sultan

    Published 2018
    “…In order to solve it, Bat Algorithm method is implement in to optimization method in fuzzy modeling for classification. …”
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    Undergraduates Project Papers
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    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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    Article
  5. 5

    Optimal route checking using genetic algorithm for UiTM's bus services / Tengku Salman Fathi Tengku Jaafar by Tengku Jaafar, Tengku Salman Fathi

    Published 2006
    “…This research study with the development of the Optimal Route Checking Using Genetic Algorithm system should solve this scenario. …”
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    Thesis
  6. 6

    Optimize class time tabling by using genetic algorithm technique in UTHM by Ahmad, Izah Rafidah

    Published 2019
    “…This research used genetic algorithm (GA) that was applied to java programming languages with a goal of reducing conflict and optimizing the fitness. …”
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    Thesis
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    Towards the utilization of normalized LMS algorithm in adaptive filter by Misbah Emhammed, Misbah Abdelsalam, Ho, Yih Hwa

    Published 2014
    “…In this paper, we focused on how the development of algorithms helped reduce the level of noise. This in turn led us to utilize the Least Mean Square (LMS) and Normalized Least Mean Square (NLMS) algorithms in order to do so. …”
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    Article
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    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…Features selection process can be considered a problem of global combinatorial optimization in machine learning. Genetic algorithm GA had been adopted to perform features selection method; however, this method could not deliver an acceptable detection rate, lower accuracy, and higher false alarm rates. …”
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    Thesis
  10. 10

    Comparison of performances of Jaya Algorithm and Cuckoo Search algorithm using benchmark functions by Ahmed, Mashuk, Nasser, Abdullah B., Kamal Z., Zamli, Heripracoyo, Sulistyo

    Published 2022
    “…Metaheuristic algorithms have been used successfully for solving different optimization problems. …”
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    Conference or Workshop Item
  11. 11

    How to Test the Means among Heteroscedastic Normal Populations by Abd. Rahman, Mohd Nawi

    Published 1988
    “…To facilitate the application of the procedure, an efficient estimation algorithm is shown for its means and the corresponding variance-covariance matrix. …”
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    Article
  12. 12

    An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

    Published 2015
    “…Feature subset selection and classifier ensemble learning are familiar techniques with high ability to optimize above problems. Recently, various techniques based on different algorithms have been developed. …”
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    Thesis
  13. 13

    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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    Article
  14. 14

    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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    Thesis
  15. 15

    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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    Thesis
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    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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    Thesis
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    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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    Conference or Workshop Item
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    Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares by Uraibi, Hassan Sami

    Published 2009
    “…In this respect, we propose to incorporate our proposed DRBLTS in the bootstrap model selection technique. We also proposed to use an alternative robust location and scale estimates which are less affected by outliers instead of using the classical mean and classical standard deviation. …”
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    Thesis
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    Adaptive interference canceller using analog algorithm with offset voltage by Mohammed, Alaa Hadi

    Published 2015
    “…They require the utilization of the adaptive algorithms. Algorithms such as Least Mean Square (LMS), Normalized Least Mean Square (NLMS) and Recursive Least Square (RLS) algorithms often have poor numerical properties due to the practical implementation complexities. …”
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    Thesis
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