Search Results - (( evolution optimization svm algorithm ) OR ( program implementation cell algorithm ))

  • Showing 1 - 11 results of 11
Refine Results
  1. 1

    Improved whale optimization algorithm for feature selection in Arabic sentiment analysis by Tubishat, Mohammad, Abushariah, Mohammad A.M., Idris, Norisma, Aljarah, Ibrahim

    Published 2019
    “…In SA, feature selection phase is an important phase for machine learning classifiers specifically when the datasets used in training is huge. Whale Optimization Algorithm (WOA) is one of the recent metaheuristic optimization algorithm that mimics the whale hunting mechanism. …”
    Get full text
    Get full text
    Article
  2. 2

    Time series predictive analysis based on hybridization of meta-heuristic algorithms by Mustaffa, Zuriani, Sulaiman, Mohd Herwan, Rohidin, Dede, Ernawan, Ferda, Kasim, Shahreen

    Published 2018
    “…The identified meta-heuristic methods namely Moth-flame Optimization (MFO), Cuckoo Search algorithm (CSA), Artificial Bee Colony (ABC), Firefly Algorithm (FA) and Differential Evolution (DE) are individually hybridized with a well-known machine learning technique namely Least Squares Support Vector Machines (LS-SVM). …”
    Get full text
    Get full text
    Article
  3. 3
  4. 4

    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]. …”
    Get full text
    Get full text
    Article
  5. 5

    Time series predictive analysis based on hybridization of meta-heuristic algorithms by Zuriani, Mustaffa, M. H., Sulaiman, Rohidin, Dede, Ernawan, Ferda, Shahreen, Kasim

    Published 2018
    “…The identified meta-heuristic methods namely Moth-flame Optimization (MFO), Cuckoo Search algorithm (CSA), Artificial Bee Colony (ABC), Firefly Algorithm (FA) and Differential Evolution (DE) are individually hybridized with a well-known machine learning technique namely Least Squares Support Vector Machines (LS-SVM). …”
    Get full text
    Get full text
    Get full text
    Article
  6. 6
  7. 7

    Stock market turning points rule-based prediction / Lersak Photong … [et al.] by Photong, Lersak, Sukprasert, Anupong, Boonlua, Sutana, Ampant, Pravi

    Published 2021
    “…Finally, rule-based optimisation techniques such as Particle Swarm Optimization (PSO), Differential Evolution (DE) and Grey Wolf Optimizer (GWO) were used to minimise the amount of time employed in the stock market turning points prediction. …”
    Get full text
    Get full text
    Book Section
  8. 8

    Optimizing tree planting areas through integer programming and improved genetic algorithm by Md Badarudin, Ismadi

    Published 2012
    “…Therefore, a hybrid algorithm through an incorporation of Integer Programming and Improved Genetic Algorithm was proposed for planting lining design. …”
    Get full text
    Get full text
    Thesis
  9. 9

    New reflector shaping methods for dual-reflector antenna by Quzwain, Kamelia, Yamada, Yoshihide, Kamardin, Kamilia, Abd Rahman, Nurul Huda, Ismail, Alyani

    Published 2022
    “…First, the equivalent parabola and circle equation is implemented in the reflector shaping algorithms. Second, a Matrix Laboratory (MATLAB) program is developed in order to obtain the main and sub reflector shapes. …”
    Get full text
    Get full text
    Article
  10. 10

    Prioritizing CD4 count monitoring in response to ART in resource-constrained settings: a retrospective application of prediction-based classification by Azzoni, Livio, Foulkes, Andrea S., Liu, Yan, Johnson, Margaret, Smith, Collette, Kamarulzaman, Adeeba, Montaner, Julio, Mounzer, Karam, Saag, Michael, Cahn, Pedro, Cesar, Carina, Krolewiecki, Alejandro, Sanne, Ian, Montaner, Luis J.

    Published 2012
    “…The model uses repeatedly measured biomarkers (white blood cell count and lymphocyte percent) to predict CD4+ T cell outcome through first-stage modeling and subsequent classification based on clinically relevant thresholds (CD4+ T cell count of 200 or 350 cells/ml). …”
    Get full text
    Get full text
    Get full text
    Article
  11. 11

    Development Of Distributed Grid-Based Hydrological Model And Floodplain Inundation Management System by Al_Fugara, A’kif Mohammed Salem

    Published 2008
    “…The simulation algorithms of the rainfall-runoff model have operated on grid bases compatible with the MATLAB programming language, which has been used to write instructions to many grid-based operations. …”
    Get full text
    Get full text
    Thesis