Search Results - intelligence based ((((model algorithm) OR (svm algorithm))) OR (modified algorithm))

Refine Results
  1. 1

    Evaluating JA-ABC5 hyperparameter optimisation with classifiers by Ravindran, Nadarajan, Noorazliza, Sulaiman, Junita, Mohamad-Saleh

    Published 2024
    “…Because of its simplicity, flexibility, and robustness, the Artificial Bee Colony (ABC) algorithm, a swarm intelligence-based optimisation method, has been widely applied in a variety of fields. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  2. 2
  3. 3

    Hybrid harmony search-artificial intelligence models in credit scoring by Goh, Rui Ying

    Published 2019
    “…With the parallelization of MHS hybrid models, the computational time is effectively reduced, with RF hybrid models faster than SVM hybrid models. …”
    Get full text
    Get full text
    Thesis
  4. 4

    Identification of transformer fault based on dissolved gas analysis using hybrid support vector machine-modified evolutionary particle swarm optimisation by Illias, Hazlee Azil, Wee, Zhao Liang

    Published 2018
    “…In this work, a hybrid support vector machine (SVM) with modified evolutionary particle swarm optimisation (EPSO) algorithm was proposed to determine the transformer fault type. …”
    Get full text
    Get full text
    Article
  5. 5
  6. 6

    Modified And Ensemble Intelligent Water Drop Algorithms And Their Applications by O. F. Alijla, Basem

    Published 2015
    “…Pertama, algoritma TAC yang diubahsuai, diperkenalkan. The Intelligent Water Drop (IWD) algorithm is a swarm-based model that is useful for undertaking optimization problems. …”
    Get full text
    Get full text
    Thesis
  7. 7
  8. 8

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

    Published 2018
    “…Methods has been proposed to construct models including machine learning algorithms such as Neural Networks (NN), Support Vector Machines (SVM) and Deep Learning. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  9. 9

    Time series data intelligent clustering algorithm for landslide displacement prediction by Han, Liu, Shang, Tao, Shu, Jisen, Khan Chowdhury, Ahmed Jalal

    Published 2018
    “…To address this problem, an intelligent clustering algorithm for time series data in landslide displacement prediction based on nonlinear dynamic time bending is proposed in this paper. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  10. 10

    Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain by Mohamad Zihin , Mohd Zain

    Published 2018
    “…Multi-objective optimization problems are also addressed by proposing a modified multi-criterion optimization algorithm based on a Pareto-based Particle Swarm Optimization (PSO) algorithm called Multi-Objective Particle Swarm Optimization (MOPSO). …”
    Get full text
    Get full text
    Thesis
  11. 11

    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. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  12. 12

    Prediction of photovoltaic system output using hybrid Cuckoo Search Least Square Support Vector Machine / Muhammad Aidil Adha Aziz by Aziz, Muhammad Aidil Adha

    Published 2019
    “…This thesis presents a practical and reliable approach for the prediction of PV power output using an intelligent-based technique namely Cuckoo Search Algorithm - Least Square Support Vector Machine (CS-LSSVM). …”
    Get full text
    Get full text
    Thesis
  13. 13
  14. 14
  15. 15
  16. 16
  17. 17
  18. 18
  19. 19
  20. 20