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  1. 1

    Classification with degree of importance of attributes for stock market data mining by Khokhar, Rashid Hafeez, Md. Sap, Mohd. Noor

    Published 2004
    “…Alan Fan et aI., [2] use Support Vector Machine (SVM) to stock market prediction. The SVM is a training algorithm for learning classification and regression rules from data [7]. …”
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    Article
  2. 2

    Y-type Random 2-satisfiability In Discrete Hopfield Neural Network by Guo, Yueling

    Published 2024
    “…During the retrieval phase, a new activation function and Swarm Mutation were proposed to ensure the diversity of the neuron states. The proposed algorithm and mutation mechanism showed optimal performances as compared to the existing algorithms. …”
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    Thesis
  3. 3

    Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets by Saeed, Sana

    Published 2019
    “…A new self-adaptive hybrid algorithm (CSCMAES) is introduced for optimization. …”
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    Thesis
  4. 4

    Support Vector Machines (SVM) in Test Extraction by Ghazali, Nadirah

    Published 2006
    “…This project's objective is to create a summarizer, or extractor, based on machine learning algorithms, which are namely SVM and K-Means. …”
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    Final Year Project
  5. 5

    Support Vector Machines (SVM) in Test Extraction by Ghazali, Nadirah

    Published 2006
    “…This project's objective is to create a summarizer, or extractor, based on machine learning algorithms, which are namely SVM and K-Means. …”
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    Final Year Project
  6. 6

    Seed disperser ant algorithm for optimization / Chang Wen Liang by Chang , Wen Liang

    Published 2018
    “…The Seed Disperser Ant Algorithm (SDAA) is developed based on the evolution or expansion process of Seed Disperser Ant (Aphaenogaster senilis) colony. …”
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    Thesis
  7. 7

    Comparative performance of machine learning algorithms for cryptocurrency forecasting by Hitam, Nor Azizah, Ismail, Amelia Ritahani

    Published 2018
    “…Machine Learning is part of Artificial Intelligence that has the ability to make future forecastings based on the previous experience. Methods has been proposed to construct models including machine learning algorithms such as Neural Networks (NN), Support Vector Machines (SVM) and Deep Learning. …”
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    Article
  8. 8

    A comparative study of clonal selection algorithm for effluent removal forecasting in septic sludge treatment plant by Ting, Sie Chun, Abdul Malik, Marlinda, Ismail, Amelia Ritahani

    Published 2015
    “…The test results of the case study showed that the prediction of the CSA-based SSTP model worked well and provided model performance as satisfactory as the LS-SVM model. …”
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    Article
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  11. 11

    Investigation of features for classification RFID reading between two RFID reader in various support vector machine kernel function by Choong, Chun Sern, Ahmad Fakhri, Ab. Nasir, P.P. Abdul Majeed, Anwar, Muhammad Aizzat, Zakaria, Mohd Azraai, Mohd Razman

    Published 2022
    “…Instead, the distance verses RSSI algorithm is used to determine the objects to be located based on the distance of the tag to be located to each reader. …”
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    Conference or Workshop Item
  12. 12
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    Non-fiducial based electrocardiogram biometrics with kernel methods by Hejazi, Maryamsadat

    Published 2017
    “…The effectiveness of this algorithm is investigated by comparing with other AC based feature extraction algorithms involving AC/LDA (Linear Discriminant Analysis) and AC/PCA (Principal Component Analysis). …”
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    Thesis
  14. 14

    GA optimization-based BRB AI reasoning algorithm for determining the factors affecting customer churn for operators by Kun, Liu, Alli, Hassan, Abd Rahman, Khairul Aidil Azlin

    Published 2024
    “…Therefore, in this paper, a belief rule base (BRB) artificial intelligence inference algorithm based on GA optimization to determine the factors affecting customer churn for operators proposed. …”
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    Article
  15. 15

    Performance improvement through optimal location and sizing of distributed generation / Zuhaila Mat Yasin by Mat Yasin, Zuhaila

    Published 2014
    “…To enhance the robustness of the algorithm, the QIEP technique is constructed based on multiobjective model in which the multiobjective functions consist of reducing power losses, increasing maximum loadability and cost minimisation. …”
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    Thesis
  16. 16

    Productivity monitoring in building construction projects: a systematic review by Alaloul, W.S., Alzubi, K.M., Malkawi, A.B., Al Salaheen, M., Musarat, M.A.

    Published 2021
    “…Machine learning algorithms (ANN, SVM) and BIM were integrated with monitoring tools and technologies to enhance the automated monitoring performance in construction productivity. …”
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    Article
  17. 17

    Productivity monitoring in building construction projects: a systematic review by Alaloul, W.S., Alzubi, K.M., Malkawi, A.B., Al Salaheen, M., Musarat, M.A.

    Published 2021
    “…Machine learning algorithms (ANN, SVM) and BIM were integrated with monitoring tools and technologies to enhance the automated monitoring performance in construction productivity. …”
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    Article
  18. 18

    Productivity monitoring in building construction projects: a systematic review by Alaloul, W.S., Alzubi, K.M., Malkawi, A.B., Al Salaheen, M., Musarat, M.A.

    Published 2022
    “…Machine learning algorithms (ANN, SVM) and BIM were integrated with monitoring tools and technologies to enhance the automated monitoring performance in construction productivity. …”
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    Article
  19. 19

    Productivity monitoring in building construction projects: a systematic review by Alaloul, W.S., Alzubi, K.M., Malkawi, A.B., Al Salaheen, M., Musarat, M.A.

    Published 2022
    “…Machine learning algorithms (ANN, SVM) and BIM were integrated with monitoring tools and technologies to enhance the automated monitoring performance in construction productivity. …”
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    Article
  20. 20

    Productivity monitoring in building construction projects: a systematic review by Alaloul, W.S., Alzubi, K.M., Malkawi, A.B., Al Salaheen, M., Musarat, M.A.

    Published 2022
    “…Machine learning algorithms (ANN, SVM) and BIM were integrated with monitoring tools and technologies to enhance the automated monitoring performance in construction productivity. …”
    Get full text
    Get full text
    Article