Search Results - (( pattern estimation using algorithm ) OR ( using simulation method algorithm ))

Refine Results
  1. 1
  2. 2

    Adaptive beamforming algorithm based on Simulated Kalman Filter by Kelvin Lazarus, Lazarus

    Published 2017
    “…There are many methods to perform adaptive beamforming and one of the method is to use metaheuristic algorithm, to estimate the weights for individual elements in an array. …”
    Get full text
    Get full text
    Thesis
  3. 3

    Parameter estimation in double exponential smoothing using genetic algorithm / Foo Fong Yeng, Lau Gee Choon and Zuhaimy Ismail by Foo, Fong Yeng, Lau, Gee Choon, Ismail, Zuhaimy

    Published 2014
    “…The objective of this research is to estimate the Double Exponential Smoothing by using Genetic Algorithm Mechanism. …”
    Get full text
    Get full text
    Research Reports
  4. 4

    Fraud detection in telecommunication using pattern recognition method / Mohd Izhan Mohd Yusoff by Mohd Yusoff, Mohd Izhan

    Published 2014
    “…The new algorithm is tested on simulated and real data where the results show it is capable of detecting fraud activities. …”
    Get full text
    Get full text
    Get full text
    Thesis
  5. 5

    Trajectory planning and simulation for 3d printing process by Ng, Chin Yong

    Published 2022
    “…The slicing method used is basic slicing. The slicing algorithm consists of two sections: intersection point tracking algorithm and contour creation algorithm. …”
    Get full text
    Get full text
    Final Year Project / Dissertation / Thesis
  6. 6

    Hybrid optimization approach to estimate random demand by Wahab, Musa, Ku-Mahamud, Ku Ruhana, Yasin, Azman

    Published 2012
    “…The main objective of this study is to develop a demand forecasting model that should reflect the characteristics of random demand patterns.To accomplish this goal, a hybrid algorithm combining a genetic algorithm and a local search algorithm method was developed to overcome premature convergence in local optima problems.The performance of the hybrid algorithm was compared with a single algorithm model in estimating parameter values that minimize objective function which was used to measure the goodness-of-fit between the observed data and simulated results.However, two problems had to be overcome in the forecasting random demand model. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  7. 7

    Effective source number enumeration approach under small snapshot numbers by Ge, Shengguo

    Published 2024
    “…Experimental results show that the SEMD-based method performs significantly better than the traditional signal source number estimation algorithm in these complex environments, especially under a small number of snapshots, the SEMD method can still maintain a high estimation accuracy. …”
    Get full text
    Get full text
    Get full text
    Thesis
  8. 8

    Determining the order of a moving average model of time series using reversible jump MCMC: a comparison between laplacian and gaussian noises by Suparman, Suparman, Abdellah Salhi, Abdellah Salhi, Rusiman, Mohd Saifullah

    Published 2020
    “…Moreover, the Bayesian method was used to estimate the parameters, such as the order and coefficient of the model, as well as noise variance. …”
    Get full text
    Get full text
    Get full text
    Article
  9. 9

    Plant recognition based on identification of leaf image using image processing / Nor Silawati Sha’ari by Sha’ari, Nor Silawati

    Published 2018
    “…ANN and KNN is applied to solve the problems in image analysis, pattern recognition and classification. For the ANN, Multilayer feed-forward networks are trained using Back Propagation (BP) learning algorithm and for the KNN, is used the most common distance which is Euclidean. …”
    Get full text
    Get full text
    Student Project
  10. 10

    Epidemiological parameter estimation of sird model for covid-19 outbreak by Muhammad Fahmi, Ahmad Zuber, Norhayati, Rosli, Noryanti, Muhammad

    Published 2022
    “…This paper is devoted to the parameter estimation of the SIRD model using the Markov Chain Monte Carlo (MCMC) method of the Metropolis Hasting algorithm. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  11. 11

    Simulation of COVID-19 outbreaks via graphical user interface (GUI) by Mohd Jamil, Norazaliza, Rosli, Norhayati, Muhammad, Noryanti

    Published 2021
    “…An improved SIRD model was solved via the 4th order Runge-Kutta (RK4) method and 14 unknown parameters were estimated by using Nelder- Mead algorithm and pattern-search technique. …”
    Get full text
    Get full text
    Get full text
    Article
  12. 12

    Parametric and Semiparametric Competing Risks Models for Statistical Process Control with Reliability Analysis by Mohamed Elfaki, Faiz Ahmed

    Published 2004
    “…The Expectation Maximization (EM) algorithm is utilized to obtain the estimate of the parameters in the models. …”
    Get full text
    Get full text
    Thesis
  13. 13

    Determining malaria risk factors in Abuja, Nigeria using various statistical approaches by Segun, Oguntade Emmanuel

    Published 2018
    “…Data collected were used for the multilevel analysis, Markov Chain Monte Carlo (MCMC) simulation via WinBUGS algorithm and influence diagrams for BBNs. …”
    Get full text
    Get full text
    Thesis
  14. 14

    Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman by Che Osman, Siti Eshah

    Published 2019
    “…Due to the center biased nature of the videos, the HPSO algorithm uses an initial pattern (hexagon-shaped) to speed up the convergence of the algorithm. …”
    Get full text
    Get full text
    Thesis
  15. 15

    Hybrid particle swarm optimization for robust digital image watermarking by Tao, Hai, Jasni, Mohamad Zain, Abdalla, Ahmed N., Mohammad Masroor, Ahmed

    Published 2011
    “…Moreover, the work takes accomplishing maximum robustness and transparency into consideration. HPSO method is used to estimate the multiple parameters involved in the model. …”
    Get full text
    Get full text
    Get full text
    Article
  16. 16

    Modelling and Forecasting the Kuala Lumpur Composite Index Rate of Returns Using Generalised Autoregressive Conditional Heteroscedasticity Models by Abdul Muthalib, Maiyastri

    Published 2004
    “…The EM algorithm is applied to split the heterogeneous data, and the estimated parameters are used to correct the outlying data using the Mahalanobis Distance. …”
    Get full text
    Get full text
    Thesis
  17. 17

    Geometrical and dimensional defect evaluation of cold forged AA6061 propeller blade by Abdullah, Ahmad Baharuddin

    Published 2013
    “…In addition, the defect was predicted by investigating the design parameters and its effect on the material flow pattern. Comparison between the simulation result and the fabricated pin head show a geometrically similar pattern. …”
    Get full text
    Get full text
    Thesis
  18. 18

    Chemometric approaches in the evaluation of trace metals in commercially raised tilapia and preliminary health risk assessment of its consumption / Low Kah Hin by Low, Kah Hin

    Published 2012
    “…For safety evaluation, the metal concentrations in the edible muscles were compared with the established legal limits and reasonable maximum exposures were simulated using the Monte Carlo algorithm.…”
    Get full text
    Get full text
    Thesis
  19. 19

    Block matching algorithms for motion estimation using modified Cross-Diamond-Hexagonal search / Abd Razak Mahmud by Mahmud, Abd Razak

    Published 2008
    “…This algorithm basically employs two crossshaped search patterns consecutively in the very beginning steps and switch using diamond-shaped patterns. …”
    Get full text
    Get full text
    Thesis
  20. 20

    Variable block based motion estimation using hexagon diamond full search algorithm (HDFSA) via block subtraction technique by Hardev Singh, Jitvinder Dev Singh

    Published 2015
    “…The fixed block matching uses the same block size throughout the motion estimation process while the variable block matching uses different block size. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis