Search Results - (( evolution classification techniques algorithm ) OR ( program implementation svm algorithm ))

Refine Results
  1. 1
  2. 2

    Implementation Of SVM For Cascaded H-Bridge Multilevel Inverters Utilizing FPGA by Al-Jewari, Maher Abd Ibrahim

    Published 2019
    “…This thesis reports the implementation of SVM in Cascaded H-Bridge Multilevel Inverter (CHMI) using Field Programmable Gate Arrays (FPGA) and analysis in-depth the performances of SVM computation on THD and fundamental component of output voltage. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  3. 3

    Lightning Fault Classification for Transmission Line Using Support Vector Machine by Asman S.H., Aziz N.F.A., Kadir M.Z.A.A., Amirulddin U.A.U., Roslan N., Elsanabary A.

    Published 2024
    “…The proposed method was implemented in the MATLAB/SIMULINK programming platform. …”
    Conference Paper
  4. 4
  5. 5

    Kernel methods and support vector machines for handwriting recognition by Ahmad A.R., Khalid M., Yusof R.

    Published 2023
    “…Finding the solution hyperplane involves using quadratic programming which is computationally intensive. Algorithms for practical implementation such as sequential minimization optimization (SMO) and its improvements are discussed. …”
    Conference paper
  6. 6

    Feature selection optimization using hybrid relief-f with self-adaptive differential evolution by Zainudin, Muhammad Noorazlan Shah, Sulaiman, Md. Nasir, Mustapha, Norwati, Perumal, Thinagaran, Ahmad Nazri, Azree Shahrel, Mohamed, Raihani, Abd Manaf, Syaifulnizam

    Published 2017
    “…Hence, feature selection is embedded to select the most meaningful features based on their rank. Differential evolution (DE) is one of the evolutionary algorithms that are widely used in various classification domains. …”
    Get full text
    Get full text
    Get full text
    Article
  7. 7
  8. 8
  9. 9
  10. 10
  11. 11

    Email spam classification based on deep learning methods: A review by Tusher, Ekramul Haque, Mohd Arfian, Ismail, Anis Farihan, Mat Raffei

    Published 2025
    “…Deep learning has become a potent collection of techniques for addressing intricate issues such as spam classification in recent times. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  12. 12

    Analysis on target detection and classification in LTE based passive forward scattering radar by Raja Abdullah, Raja Syamsul Azmir, Abdul Aziz, Noor Hafizah, Abdul Rashid, Nur Emileen, Salah, Asem Ahmad, Hashim, Fazirulhisyam

    Published 2016
    “…By utilizing the forward scattering technique and procedure into the specific mode of PBR can provide an improvement in target detection and classification. …”
    Get full text
    Get full text
    Get full text
    Article
  13. 13
  14. 14

    Improving Ant Swarm Optimization With Embedded Vaccination For Optimum Reducts Generation by Pratiwi, Lustiana, Choo, Yun Huoy, Draman @ Muda, Azah Kamilah, Draman @ Muda, Noor Azilah

    Published 2011
    “…Unlike a conventional PSOIACO algorithm, this hybrid algorithm shows improvement of the classification accuracy in its generated rough reducts to solve NP-Hard problem. …”
    Get full text
    Get full text
    Conference or Workshop Item
  15. 15

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

    Published 2014
    “…Finally, a novel hybrid Quantum-Inspired Evolutionary Programming - Least-Squares Support Vector Machine (QIEP-SVM) was presented. …”
    Get full text
    Get full text
    Thesis
  16. 16

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

    Published 2004
    “…The SVM is a training algorithm for learning classification and regression rules from data [7]. …”
    Get full text
    Get full text
    Article
  17. 17

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

    Published 2021
    “…From news classification and news sentiment, a rule-based algorithm was used to predict the stock market turning points. …”
    Get full text
    Get full text
    Book Section
  18. 18

    Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm by Hasan, Shafaatunnur, Tan, Swee Quo, Shamsuddin, Siti Mariyam, Sallehuddin, Roselina

    Published 2011
    “…Artificial Neural Network (ANN) is a new information processing system with large quantity of highly interconnected neurons or elements processing parallel to solve problems.Recently, evolutionary computation technique, Artificial Fish Swarm Algorithm (AFSA) is chosen to optimize global searching of ANN.In optimization process, each Artificial Fish (AF) represents a neural network with output of fitness value.The AFSA is used in this study to analyze its effectiveness in enhancing Multilayer Perceptron (MLP) learning compared to Particle Swarm Optimization (PSO) and Differential Evolution (DE) for classification problems.The comparative results indeed demonstrate that AFSA show its efficient, effective and stability in MLP learning.…”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  19. 19

    Classification of Immunosignature Using Random Forests for Cancer Diagnosis by Zarzar, Mouayad, Razak, Eliza, Htike@Muhammad Yusof, Zaw Zaw, Yusof, Faridah

    Published 2015
    “…To attain this essential research purpose, a minimum set of genes that can assure higher performance in classification using data mining algorithms need to be detected. …”
    Get full text
    Get full text
    Get full text
    Proceeding Paper
  20. 20

    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. …”
    Get full text
    Get full text
    Thesis