Search Results - (( variable equation modeling algorithm ) OR ( java application optimized algorithm ))

Refine Results
  1. 1

    SURE-Autometrics algorithm for model selection in multiple equations by Norhayati, Yusof

    Published 2016
    “…Thus, this study aims to develop an algorithm for model selection in multiple equations focusing on seemingly unrelated regression equations (SURE) model. …”
    Get full text
    Get full text
    Get full text
    Thesis
  2. 2

    Sure (EM)-Autometrics: An Automated Model Selection Procedure with Expectation Maximization Algorithm Estimation Method (S/O 14925) by Kamarudin, Nur Azulia

    Published 2021
    “…Hence, the integration of EM algorithm estimation is applicable in improving the performance of automated model selection procedures for multiple equations models…”
    Get full text
    Get full text
    Monograph
  3. 3
  4. 4

    Performance evaluation of real-time multiprocessor scheduling algorithms by Alhussian, H., Zakaria, N., Abdulkadir, S.J., Fageeri, S.O.

    Published 2016
    “…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
    Get full text
    Get full text
    Conference or Workshop Item
  5. 5

    Assessing the simulation performances of multiple model selection algorithm by Yusof, Norhayati, Ismail, Suzilah, Tuan Muda, Tuan Zalizam

    Published 2015
    “…The capability of the algorithm in finding the true specification of multiple models is measured by the percentage of simulation outcomes.Overall results show that the algorithm has performed well for a model with two equations.The findings also indicated that the number of variables in the true models affect the algorithm performances. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  6. 6

    Route Optimization System by Zulkifli, Abdul Hayy

    Published 2005
    “…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
    Get full text
    Get full text
    Final Year Project
  7. 7

    Extended multiple models selection algorithms based on iterative feasible generalized least squares (IFGLS) and expectation-maximization (EM) algorithm by Nur Azulia, Kamarudin

    Published 2019
    “…The simulation results indicated that performance of SURE(IFGLS)-Autometrics and SURE(EM)-Autometrics algorithms improved in conditions of large sample, strong correlation among equations, small GUMS, a smaller number of equations, tight significance level and in an empty model (without predictor variables). …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  8. 8
  9. 9
  10. 10
  11. 11

    Variable order variable stepsize algorithm for solving nonlinear Duffing oscillator by Rasedee, Ahmad Fadly Nurullah, Ishak, Norizarina, Hamzah, Siti Raihana, Ijam, Hazizah Mohd, Suleiman, Mohamed, Ibrahim, Zarina Bibi, Sathar, Mohammad Hasan Abdul, Ramli, Nur Ainna, Kamaruddin, Nur Shuhada

    Published 2017
    “…The Duffling oscillator is a type of nonlinear higher order differential equation. In this research, a numerical approximation for solving the Duffing oscillator directly is introduced using a variable order stepsize (VOS) algorithm coupled with a backward difference formulation. …”
    Get full text
    Get full text
    Get full text
    Article
  12. 12

    Weather prediction in Kota Kinabalu using linear regressions with multiple variables by Teong, Khan Vun, Chung, Gwo Chin, Jedol Dayou

    Published 2021
    “…Numerical weather prediction is the process of using existing numerical data on weather conditions to forecast the weather using machine learning algorithms. This study employs machine learning algorithms, a linear regression model using statistics, and two optimization approaches, the normal equation approach, and gradient descent approach to predict the weather based on a few variables. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Proceedings
  13. 13
  14. 14
  15. 15

    Taguchi?s T-method with Normalization-Based Binary Bat Algorithm by Marlan Z.M., Jamaludin K.R., Harudin N.

    Published 2025
    “…s orthogonal array is used as a variable selection approach in optimizing the predictive model. …”
    Conference paper
  16. 16
  17. 17

    An effective spectral approach to solving fractal differential equations of variable order based on the non-singular kernel derivative by Basim, M., Senu, N., Ahmadian, A., Ibrahim, Z. B., Salahshour, S.

    Published 2023
    “…A new differential operators class has been discovered utilising fractional and variable-order fractal Atangana-Baleanu derivatives that have inspired the develop-ment of differential equations new class. …”
    Get full text
    Get full text
    Article
  18. 18

    Independent And Dependent Job Scheduling Algorithms Based On Weighting Model For Grid Environment by M. Al-Najjar, Hazem

    Published 2018
    “…The resulting model is then applied onto the independent and dependent job scheduling algorithms to verify the capability of proposed job scheduling model in a real environment. …”
    Get full text
    Get full text
    Thesis
  19. 19

    Variable order variable stepsize algorithm for solving nonlinear Duffing oscillator by Nurullah Rasedee A.F., Ishak N., Hamzah S.R., Ijam H.M., Suleiman M., Ibrahim Z.B., Abdul Sathar M.H., Ramli N.A., Kamaruddin N.S.

    Published 2024
    “…The Duffling oscillator is a type of nonlinear higher order differential equation. In this research, a numerical approximation for solving the Duffing oscillator directly is introduced using a variable order stepsize (VOS) algorithm coupled with a backward difference formulation. …”
    Article
  20. 20

    Algorithmic approaches in model selection of the air passengers flows data by Ismail, Suzilah, Yusof, Norhayati, Tuan Muda, Tuan Zalizam

    Published 2015
    “…Algorithm is an important element in any problem solving situation.In statistical modelling strategy, the algorithm provides a step by step process in model building, model testing, choosing the ‘best’ model and even forecasting using the chosen model.Tacit knowledge has contributed to the existence of a huge variability in manual modelling process especially between expert and non-expert modellers.Many algorithms (automated model selection) have been developed to bridge the gap either through single or multiple equation modelling.This study aims to evaluate the forecasting performances of several selected algorithms on air passengers flow data based on Root Mean Square Error (RMSE) and Geometric Root Mean Square Error (GRMSE).The findings show that multiple models selection performed well in one and two step-ahead forecast but was outperformed by single model in three step-ahead forecasts.…”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item