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  1. 1
    Weather prediction in Kota Kinabalu using linear regressions with multiple variables

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

    Published 2021
    “…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. …”
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  2. 2
    Determination of tree stem volume : A case study of Cinnamomum

    Determination of tree stem volume : A case study of Cinnamomum by Noraini Abdullah

    Published 2013
    “…Illustrations and algorithms are incorporated into the procedures. Non-normal and nonlinear data variables are addressed, hence data characterization is presented. …”
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  3. 3
    Study on numerical solution of a variable order fractional differential equation based on symmetric algorithm

    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. …”
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  4. 4
    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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  5. 5
    Two-Point Block Variable Order Step Size Multistep Method for Solving Higher Order Ordinary Differential Equations Directly

    Two-Point Block Variable Order Step Size Multistep Method for Solving Higher Order Ordinary Differential Equations Directly by Ahmad Fadly Nurullah Rasedee, Mohammad Hasan Abdul Sathar, Siti Raihana Hamzah, Norizarina Ishak, Tze Jin Wong, Lee Feng Koo, Siti Nur Iqmal Ibrahim

    Published 2024
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  6. 6
    Parallel method using MPI for solving large systems of delay differential equations

    Parallel method using MPI for solving large systems of delay differential equations by Ishak, Fuziyah, Suleiman, Mohamed

    Published 2012
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  7. 7
    Algorithm enhancement for host-based intrusion detection system using discriminant analysis

    Algorithm enhancement for host-based intrusion detection system using discriminant analysis by Dahlan, Dahliyusmanto

    Published 2004
    “…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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  8. 8
    Variable order variable stepsize algorithm for solving nonlinear Duffing oscillator

    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. …”
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  9. 9
    Variable order variable stepsize algorithm for solving nonlinear Duffing oscillator

    Variable order variable stepsize algorithm for solving nonlinear Duffing oscillator by Rasedee, AFN, Ishak, N, Hamzah, SR, Ijam, HM, Suleiman, M, Ibrahim, ZB, Sathar, MHA, Ramli, NA, Kamaruddin, NS

    Published 2024
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  10. 10
    A Numerical Algorithm for Solving Stiff Ordinary Differential Equations

    A Numerical Algorithm for Solving Stiff Ordinary Differential Equations by Yatim, S. A. M., Ibrahim, Z. B., Othman, K. I., Suleiman, M. B.

    Published 2012
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  11. 11
    Numerical algorithm of block method for general second order ODEs using variable step size

    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). …”
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  12. 12
    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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  13. 13
    Two-point block backward differentiation formula for solving higher order ordinary differential equations

    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. …”
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  14. 14
    Numerical algorithm of block method for general second order ODEs using variable step size

    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). …”
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  15. 15
    A numerical algorithm for solving stiff ordinary differential equations

    A numerical algorithm for solving stiff ordinary differential equations by Mohd Yatim, Siti Ainor, Ibrahim, Zarina Bibi, Othman, Khairil Iskandar, Suleiman, Mohamed

    Published 2013
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  16. 16
    Assessing the simulation performances of multiple model selection algorithm

    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. …”
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  17. 17
    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
    “…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. …”
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  18. 18
    Classification of Cardiac Disorders Based on Electrocardiogram Data with Fuzzy Cognitive Map (FCM) Algorithm Approach

    Classification of Cardiac Disorders Based on Electrocardiogram Data with Fuzzy Cognitive Map (FCM) Algorithm Approach by Sumiati, ., Hoga, Saragih, T.K.A, Rahman, Viktor Vekky, Ronald Repi, Agung, Triayudi

    Published 2021
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  19. 19
    The effect of dose calculation algorithms on the normal tissue complication probability values of thoracic cancer

    The effect of dose calculation algorithms on the normal tissue complication probability values of thoracic cancer by Ahmad, Noor Ashikin

    Published 2015
    “…Purpose: To identify the effect of dose calculation algorithms on the Normal Tissue Complication Probability values of thoracic cancer. …”
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  20. 20
    A study on advanced statistical analysis for network anomaly detection

    A study on advanced statistical analysis for network anomaly detection by Ngadi, Md. Asri, Idris, Mohd. Yazid, Abdullah, Abd. Hanan

    Published 2005
    “…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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