Search Results - (( data integration method algorithm ) OR ( variable equations using algorithm ))

Refine Results
  1. 1

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

    Published 2021
    “…Hence, this study concentrates on an automated model selection procedure for the SURE model by integrating the expectation-maximization (EM) algorithm estimation method, named SURE(EM)-Autometrics. …”
    Get full text
    Get full text
    Monograph
  2. 2

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

    Published 2019
    “…This extension of Autometrics for model selection was also developed for multiple equations by integrating it with seemingly unrelated regressions equations (SURE) and estimated using feasible generalized least squares (FGLS), known as SURE-Autometrics algorithm. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  3. 3

    Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

    Published 2018
    “…In the developed feature selection approach, multi-objective binary-valued backtracking search algorithm (MOBBSA) is used as an efficient evolutionary search algorithm to search within different combinations of input variables and selects the non-dominated feature subsets, which minimize simultaneously both the estimation error and the number of features. …”
    Get full text
    Get full text
    Get full text
    Thesis
  4. 4

    What drives Chinese youth to use fitness-related health information on social media? an analysis of intrinsic needs, social media algorithms, and source credibility by Zhang, Xin, Tang, Qing Qing, Cai, Ying Ying

    Published 2024
    “…Data were analyzed using Partial Least Squares-Structural Equation Modeling (PLS-SEM) to examine the relationships between variables. …”
    Get full text
    Get full text
    Get full text
    Article
  5. 5

    Modelling of Adsorption of Dyes from Aqueous Solution by Activated Carbon by Wong, Teck Ngin

    Published 2004
    “…These v sets of ODEs are then integrated using the numerical algorithm DIVPAG (IMSL library subroutine), which is based on variable order, variable step method implementing backward differential formula (Gear’s Method) and is suitable for stiff system of first order non-linear ODEs. …”
    Get full text
    Get full text
    Thesis
  6. 6

    Optical soliton perturbation with quadratic-cubic nonlinearity / Mir Asma by Mir, Asma

    Published 2020
    “…These perturbation terms are mostly of Hamiltonian type that permits integrability of the perturbed NLSE. The spectrum of soliton solutions, that emerge from these algorithms are of bright, dark singular and combo solitons, which depends on the sign of discriminant and these findings are illustrated numerically too. …”
    Get full text
    Get full text
    Get full text
    Thesis
  7. 7

    Intelligence Integration Of Particle Swarm Optimization And Physical Vapour Deposition For Tin Grain Size Coating Process Parameters by Abdul Syukor, Mohamad Jaya, Mu*ath Ibrahim, Mohammad Jarrah, Mohd Asyadi Azam, Mohd Abid, Mohd Razali, Muhamad

    Published 2016
    “…Additionally,analysis of variance (ANOVA) was used to determine the significant factors influencing resultant TiN coating grain size.Based on that,a quadratic polynomial model equation was developed to represent the process variables and coating grain size.Then,in order to optimize the coating process parameters,genetic algorithms (GAs) were combined with the RSM quadratic model and used for optimization work.Finally,the models were validated using actual testing data to measure model performances in terms of residual error and prediction interval (PI).The result indicated that for RSM,the actual coating grain size of validation runs data fell within the 95% (PI) and the residual errors were less than 10 nm with very low values, the prediction accuracy of the model is 96.09%.In terms of optimization and reduction the experimental data,GAs could get the best lowest value for grain size then RSM with reduction ratio of ≈6%, ≈5%, respectively.…”
    Get full text
    Get full text
    Get full text
    Article
  8. 8

    Enhancing reservoir simulation models with genetic algorithm optimized neural networks across diverse climatic zones / Saad Mawlood Saab by Saad Mawlood , Saab

    Published 2025
    “…The research improved the predictive models by integrating them with the Genetic Algorithm (GA). The optimizer algorithm (i.e., GA) determines the optimal input variables and internal parameters in the prediction models. …”
    Get full text
    Get full text
    Get full text
    Thesis
  9. 9

    Study on numerical solution of a variable order fractional differential equation based on symmetric algorithm by Liu, Jingrui, Pan, Dongyang

    Published 2019
    “…A fully symmetric classification of the boundary value problem for a class of fractional differential equations with variable sequences is determined by using a fully symmetric differential sequence sorting algorithm. …”
    Get full text
    Get full text
    Get full text
    Article
  10. 10

    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
  11. 11
  12. 12
  13. 13

    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
    “…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
  14. 14
  15. 15
  16. 16

    Numerical algorithm of block method for general second order ODEs using variable step size by Nazreen Waeleh, Zanariah Abdul Majid

    Published 2017
    “…This paper outlines an alternative algorithm for solving general second order ordinary differential equations (ODEs). …”
    Get full text
    Get full text
    Get full text
    Article
  17. 17

    Two-point block backward differentiation formula for solving higher order ordinary differential equations by Zainuddin, Nooraini

    Published 2011
    “…Finally, this thesis zooms into the implementation of the BBDF method using the variable order algorithm for the solution of second order stiff ODEs directly. …”
    Get full text
    Get full text
    Thesis
  18. 18

    Numerical algorithm of block method for general second order ODEs using variable step size by Waeleh, Nazreen, Abdul Majid, Zanariah

    Published 2017
    “…This paper outlines an alternative algorithm for solving general second order ordinary differential equations (ODEs). …”
    Get full text
    Get full text
    Get full text
    Article
  19. 19
  20. 20

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

    Published 2015
    “…The Autometrics is an algorithm for single equation model selection.It is a hybrid method which combines expanding and contracting search techniques.In this study, the algorithm is extended for multiple equations modelling known as SURE-Autometrics.The aim of this paper is to assess the performance of the extended algorithm using various simulation experiment conditions. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item