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  1. 1

    Improved Genetic Algorithm Multilayer Perceptron Network For Data Classification by Ahmad, Fadzil

    Published 2017
    “…The results demonstrate the effectiveness of the new algorithms in term of test accuracy percentage. …”
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    Thesis
  2. 2

    Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms by Alswaitti, Mohammed Y. T.

    Published 2018
    “…Unfortunately, these algorithms suffer with several drawbacks such as the tendency to be trapped or stagnate into local optima and slow convergence rates. …”
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    Thesis
  3. 3

    A novelty classification model for varied agarwood oil quality using the K-Nearest Neighbor algorithm / Aqib Fawwaz Mohd Amidon … [et al.] by Mohd Amidon, Aqib Fawwaz, Mohd Huzir, Siti Mariatul Hazwa, Mohd Yusoff, Zakiah, Ismail, Nurlaila, Taib, Mohd Nasir

    Published 2022
    “…Among other things, it will cause the health of those involved to be affected, require a long period of time to assess one by one, and certainly contribute to high operating costs. As a result, a new grading system based on artificial algorithms, namely K-Nearest Neighbor algorithms, was established. …”
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    Book Section
  4. 4

    A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

    Published 2023
    “…The first research objective is to develop a new deep learning algorithm by a hybrid of DNN and K-Means Clustering algorithms for estimating the Lorenz chaotic system. …”
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    Thesis
  5. 5

    Travel place recommendation system using K-Nearest Neighbors algorithm / Nur Amirah Shahidan by Shahidan, Nur Amirah

    Published 2021
    “…As a conclusion, Travel Place Recommendation System has been successfully developed by using the attributes of the system which is place rating. The algorithm used in the recommendation system has been evaluated by using MAE, MSE and RMSE to calculate the accuracy of the algorithm. …”
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    Thesis
  6. 6

    Detection of leak size and its location in a water distribution system by using K-NN / Nasereddin Ibrahim Sherksi by Sherksi, Nasereddin Ibrahim

    Published 2020
    “…The successfully achieved four set objectives inclusive of (1) a new classification model to detect water leakage, (2) analysis of the effects of leakage size on the variables within a WDS, i.e. flow, pressure, pipe volume, velocity and water demand, (3) locating and specifying the leakage size in the WDS, and (4) evaluate the performance of the designed K-NN algorithm for accurate leak detection. …”
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    Thesis
  7. 7

    An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM) by Shamim, Akhtar

    Published 2024
    “…It is a well-established fact that machine learning is outperforming in terms of prediction and classification. Therefore, in this study a new optimized variant of machine learning algorithms is presented. …”
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    Thesis
  8. 8

    Multi-label risk diabetes complication prediction model using deep neural network with multi-channel weighted dropout by Dzakiyullah, Nur Rachman

    Published 2025
    “…This study contributes to the field by proposing a new regularization technique, demonstrating the effectiveness of the Algorithm Adaptation framework, and providing insights into the associations between diabetes complications. …”
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    Thesis
  9. 9

    The classification of wink-based eeg signals by means of transfer learning models by Jothi Letchumy, Mahendra Kumar

    Published 2021
    “…The results obtained from the TL-ML pipelines were evaluated in terms of classification accuracy, Precision, Recall, F1-Score and confusion matrix. …”
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    Thesis
  10. 10

    Adaptive method to improve web recommendation system for anonymous users by Almurtadha, Yahya Mohammed

    Published 2011
    “…The second is Adaptive Web page Recommendation System (AWRS) which combines the classification algorithm of iPACT in addition to the ability of adaptive recommending due to the changes of the users‟ interests and weighting methods to deal with unvisited or new added pages. …”
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    Thesis
  11. 11
  12. 12

    Breast cancer detection by using associative classifier with rule refinement method based on relevance feedback by Abubacker, Nirase Fathima, Azman, Azreen, Doraisamy, Shyamala, Azmi Murad, Masrah Azrifah

    Published 2022
    “…Several researchers have proposed the use of associative classifier that generates strong associations between features and reveals hidden relationship that can be missed by other classification algorithms. …”
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    Article
  13. 13

    An enhanced gated recurrent unit with auto-encoder for solving text classification problems by Zulqarnain, Muhammad

    Published 2020
    “…Therefore, in this research, a new model namely Encoder Simplified GRU (ES-GRU) is proposed to reduce dimension of data using an Auto-Encoder (AE). …”
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    Thesis
  14. 14

    DATA CLASSIFICATION SYSTEM WITH FUZZY NEURAL BASED APPROACH by LUONG, TRUNG TUAN

    Published 2005
    “…The project's objective is identifying the available data mining algorithms in data classification and applying new data mining algorithm to perform classification tasks. …”
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    Final Year Project
  15. 15

    Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach by Moheb Pour, Majid Reza

    Published 2009
    “…The experimental results on artificial data sets and real-world data sets (from UCI Repository) show that the new method could improve both the efficiency and accuracy of pattern classification. …”
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    Thesis
  16. 16

    New Learning Models for Generating Classification Rules Based on Rough Set Approach by Al Shalabi, Luai Abdel Lateef

    Published 2000
    “…For the problem of missing data, a new approach was proposed based on data partitioning and function mode. …”
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    Thesis
  17. 17

    Application of Optimization Methods for Solving Clustering and Classification Problems by Shabanzadeh, Parvaneh

    Published 2011
    “…Samples in the same cluster have the same label. The aim of data classification is to set up rules for the classification of some observations that the classes of data are supposed to be known. …”
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    Thesis
  18. 18

    A Novel Approach to Estimate Diffuse Attenuation Coefficients for QuickBird Satellite Images: A Case Study at Kish Island, the Persian Gulf. by Pradhan, Biswajeet, Mohd Shafri, Helmi Zulhaidi, Mansor, Shattri, Kabiri, Keivan, Samim-Namin, Kaveh

    Published 2013
    “…Diffuse attenuation coefficient (k d ) is a critical parameter for benthic habitat mapping using remotely sensed data. This research attempted to develop a new approach to estimate k d in blue and green bands of QuickBird satellite image based on the integration of Lyzenga’s method and updated NASA-k d 490 algorithm. …”
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    Article
  19. 19

    An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani by Ab Ghani, Nur Laila

    Published 2015
    “…The urban growth images obtained are analysed to improve existing classification algorithms. The improved algorithm is constructed by adding new parameter and classification rule to existing algorithm. …”
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    Thesis
  20. 20

    Enhancing Classification Algorithms with Metaheuristic Technique by Cokro, Nurwinto, Tri Basuki, Kurniawan, Misinem, ., Tata, Sutabri, Yesi Novaria, Kunang

    Published 2024
    “…Classification is a process of grouping or placing data into appropriate categories or classes based on specificattributes or features to predict labels or classes of new data based on patternsobserved from previously trained data. …”
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    Article