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  1. 1
    SURE-Autometrics algorithm for model selection in multiple equations

    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. …”
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  2. 2
    Extended multiple models selection algorithms based on iterative feasible generalized least squares (IFGLS) and expectation-maximization (EM) algorithm

    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 empirical results for both algorithms performed well as compared to other models selection procedures, particularly using WQI data where the sample size is bigger and has good quality data. …”
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  3. 3
    Field data-based mathematical modeling by Bode equations and vector fitting algorithm for renewable energy applications

    Field data-based mathematical modeling by Bode equations and vector fitting algorithm for renewable energy applications by Sabry, Ahmad H., Wan Hasan, Wan Zuha, Ab Kadir, M. Zainal A., Mohd Radzi, Mohd Amran, Shafie, Suhaidi

    Published 2018
    “…This paper proposes a new modified methodology presented as a parametric technique to determine the system’s modeling equations based on the Bode plot equations and the vector fitting (VF) algorithm by fitting the experimental data points. …”
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  4. 4
    Multiple equations model selection algorithm with iterative estimation method

    Multiple equations model selection algorithm with iterative estimation method by Kamarudin, Nur Azulia, Ismail, Suzilah

    Published 2016
    “…In particular, an algorithm on model selection for seemingly unrelated regression equations model using iterative feasible generalized least squares estimation method is proposed. …”
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  5. 5
    Sure (EM)-Autometrics: An Automated Model Selection Procedure with Expectation Maximization Algorithm Estimation Method (S/O 14925)

    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…”
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  6. 6
    Study and Implementation of Data Mining in Urban Gardening

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…The process begins through the monitoring of plants using sensors connected to the Arduino device. Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. …”
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  7. 7
    Structural Equation Modeling Algorithm and Its Application in Business Analytics

    Structural Equation Modeling Algorithm and Its Application in Business Analytics by Sorooshian, Shahryar

    Published 2017
    “…Structural Equation Modeling (SEM) is a statistical-based multivariate modeling methods, Application of SEM is similar but more powerful than regression analysis; and number of scientists using SEM in their research is rupidly inereasing. …”
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  8. 8
    Parallel Implementation of Two Level Barotropic Models Applied to the Weather Prediction Problem

    Parallel Implementation of Two Level Barotropic Models Applied to the Weather Prediction Problem by Bahri, Susila

    Published 2004
    “…Then, the system of equations is solved using Gauss Seidel method. To process the data collected from British Atmospheric Data Centre (BADC), the sequential programs in row and columnwise fashions are developed and implemented. …”
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  9. 9
    Sampling weight adjustments in partial least squares structural equation modeling: guidelines and illustrations

    Sampling weight adjustments in partial least squares structural equation modeling: guidelines and illustrations by Cheah, Jun Hwa, Roldan, Jose L., Ciavolino, Enrico, Ting, Hiram, Ramayah, T.

    Published 2020
    “…Applications of partial least squares structural equation modelling (PLS-SEM) often draw on survey data. …”
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  10. 10
    Parallel algorithms for numerical simulations of EHD ion-drag micropump on distributed parallel computing systems

    Parallel algorithms for numerical simulations of EHD ion-drag micropump on distributed parallel computing systems by Shakeel Ahmed, Kamboh

    Published 2014
    “…A data parallel algorithm (DPA-EHD) is designed and implemented for the EHD equations. …”
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  11. 11
    Algorithmic approaches in model selection of the air passengers flows data

    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.…”
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  12. 12
    Design Of Robot Motion Planning Algorithm For Wall Following Robot

    Design Of Robot Motion Planning Algorithm For Wall Following Robot by Ali Hassan, Muhamad Khairul

    Published 2006
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  13. 13
    Stochastic And Modified Sequent Peak Algorithm For Reservoir Planning Analysis Considering Performance Indices

    Stochastic And Modified Sequent Peak Algorithm For Reservoir Planning Analysis Considering Performance Indices by Oskoui, Issa Saket

    Published 2016
    “…This study is on modeling the critical period and total storage capacity of reservoir systems employing performance criteria and synthetic data generation technique. …”
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  14. 14
    Hysteresis Modelling of Pneumatic Artificial Muscle using General Cubic Equation and Factor Theorem Prediction Method / Mohd Azuwan Mat Dzahir...[et al.]

    Hysteresis Modelling of Pneumatic Artificial Muscle using General Cubic Equation and Factor Theorem Prediction Method / Mohd Azuwan Mat Dzahir...[et al.] by Mat Dzahir, Mohd Azuwan, Mat Dzahir, Mohd Azwarie, Hussein, Mohamed, Ahmad, Zair Asrar, Mohamad, Maziah, Mad Saad, Shaharil

    Published 2017
    “…The generated hysteresis models and hysteresis data obtained from experimental study were compared to verify the reliability of the proposed hysteresis modelling prediction method. …”
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  15. 15
    Ball surface representations using partial differential equations

    Ball surface representations using partial differential equations by Kherd, Ahmad Saleh Abdullah

    Published 2015
    “…Over two decades ago, geometric modelling using partial differential equations (PDEs) approach was widely studied in Computer Aided Geometric Design (CAGD). …”
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  16. 16
    A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption

    A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

    Published 2023
    “…The Lorenz Attractor is a mathematical model that describes a chaotic system. It is a solution to a set of differential equations known as the Lorenz Equations, which Edward N. …”
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  17. 17
    Development of group method of data handling based on genetic algorithm to predict incipient motion in rigid rectangular storm water channel

    Development of group method of data handling based on genetic algorithm to predict incipient motion in rigid rectangular storm water channel by Ebtehaj, I., Bonakdari, H., Khoshbin, F., Hin, Ch. Joo Bong, Ab Ghanid, A.

    Published 2017
    “…Using three di erent sources ofexperimental data and GMDH-GA model, a new equation is proposed to predict incipientmotion. …”
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  18. 18
    Qualitative study of riccati difference equation on maneuvering target tracking and fault diagnosis of wind turbine gearbox

    Qualitative study of riccati difference equation on maneuvering target tracking and fault diagnosis of wind turbine gearbox by Sumathy, M., Kilicman, Adem, Manuel, M. Maria Susai, Mary, Jesintha, Pham, Duc

    Published 2019
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  19. 19
    Development of group method of data handling based on genetic algorithm to predict incipient motion in rigid rectangular storm water channel

    Development of group method of data handling based on genetic algorithm to predict incipient motion in rigid rectangular storm water channel by Bong, Charles Hin Joo, Isa, Ebtehajaj, Hossein, Bonakdari, Fatemeh, Khoshbin, Aminuddin, Bin Ab Ghani

    Published 2017
    “…Using three di�erent sources of experimental data and GMDH-GA model, a new equation is proposed to predict incipient motion. …”
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  20. 20
    Implementation of UPFC model into fast decoupled load flow

    Implementation of UPFC model into fast decoupled load flow by Mokhlis, Hazlie, Nor, K.M.

    Published 2004
    “…This paper describes the implementation of Unified Power Flow Controller (UPFC) steady-state model into Fast Decoupled load flow analysis. The model is integrated through sequential approach, where equations for solving these devices are separated from the basic Fast Decoupled equations. …”
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