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  1. 1
    Direct approach for mining association rules from structured XML data

    Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

    Published 2012
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  2. 2
    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection

    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection by Saputra , Dhany, Rambli, Dayang R.A., Foong, Oi Mean

    Published 2008
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  3. 3
    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
    “…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
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  4. 4
    Mining Sequential Patterns Using I-PrefixSpan

    Mining Sequential Patterns Using I-PrefixSpan by Dhany , Saputra, Rambli Dayang, R.A., Foong, Oi Mean

    Published 2007
    “…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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  5. 5
    A web-based implementation of k-means algorithms

    A web-based implementation of k-means algorithms by Lee, Quan

    Published 2022
    “…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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  6. 6
    Fault diagnostic algorithm for precut fractionation column

    Fault diagnostic algorithm for precut fractionation column by Heng, H. Y., Ali, Mohamad Wijayanuddin, Kamsah, Mohd. Zaki

    Published 2004
    “…The fault diagnostic algorithm is supported by the process history based method and developed by using Borland C++ Builder 6.0. …”
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  7. 7
    Partial fraction expansion based frequency weighted balanced singular perturbation approximation model reduction technique with error bounds

    Partial fraction expansion based frequency weighted balanced singular perturbation approximation model reduction technique with error bounds by Kumar, Deepak, Haja Mohideen, Ahmad Jazlan, Sreeram, Victor, Togneri, Roberto

    Published 2016
    “…In this paper a new frequency weighted partial fraction expansion based model reduction technique is developed based on the partial fraction expansion approach. …”
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  8. 8
    Mining Sequential Patterns using I-PrefixSpan

    Mining Sequential Patterns using I-PrefixSpan by Saputra , Dhany, Dayang R.A. Rambli, Foong, Oi Mean

    Published 2008
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  9. 9
    A new modern scheme for solving fractal–fractional differential equations based on deep feedforward neural network with multiple hidden layer

    A new modern scheme for solving fractal–fractional differential equations based on deep feedforward neural network with multiple hidden layer by Admon, Mohd Rashid, Senu, Norazak, Ahmadian, Ali, Majid, Zanariah Abdul, Salahshour, Soheil

    Published 2024
    “…The recent development of knowledge in fractional calculus introduced an advanced superior operator known as fractal–fractional derivative (FFD). …”
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  10. 10
    A COMPUTATIONAL ALGORITHM for the NUMERICAL SOLUTION of NONLINEAR FRACTIONAL INTEGRAL EQUATIONS

    A COMPUTATIONAL ALGORITHM for the NUMERICAL SOLUTION of NONLINEAR FRACTIONAL INTEGRAL EQUATIONS by Amin, R., Senu, N., Hafeez, M.B., Arshad, N.I., Ahmadian, A.L.I., Salahshour, S., Sumelka, W.

    Published 2022
    “…In this paper, we develop a numerical method for the solution of nonlinear fractional integral equations (NFIEs) based on Haar wavelet collocation technique (HWCT). …”
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  11. 11
    Development of a rule-based fault diagnostic advisory system for precut fractionation column

    Development of a rule-based fault diagnostic advisory system for precut fractionation column by Heng, Han Yann

    Published 2005
    “…Although the scheme was developed based on data of fatty acid precut fractionation column, the algorithm of fault detection and diagnosis can be extended to other chemical process by changing the x-MR chart and HAZOP for each selected monitoring variables.…”
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  12. 12
    On fractional and semi-soft handover in long term evolution(LTE) networks

    On fractional and semi-soft handover in long term evolution(LTE) networks by Hussein, Yaseein Soubhi, Mohd Ali, Borhanuddin, Varahram, Pooria

    Published 2011
    “…In this paper a hybrid HO algorithms called semi-soft handover (SSHO) and fractional soft handover (FSHO) in long term evolution (LTE) system are studied. …”
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  13. 13
    A computational algorithm for the numerical solution of nonlinear fractional integral equations

    A computational algorithm for the numerical solution of nonlinear fractional integral equations by Amin, Rohul, Senu, Norazak, Hafeez, Muhammad Bilal, Arshad, Noreen Izza, Ahmadian, Ali, Salahshour, Soheil, Sumelka, Wojciech

    Published 2021
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  14. 14
    Hazard identification on fractionation column using rule based expert system

    Hazard identification on fractionation column using rule based expert system by Mohd Yunus, Mohd Yusri, Ali, Mohamad Wijayanuddin

    Published 2001
    “…The algorithm is found applicable for any of process system, however the expert system developed is only limited to the application for fractionation column of oleo chemical plant.…”
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  15. 15
    Approximation techniques

    Approximation techniques by Bingi, K., Ibrahim, R., Karsiti, M.N., Hassan, S.M., Harindran, V.R.

    Published 2020
    “…Hence, for achieving the approximated integer-order transfer function of the fractional-order system or controller, a novel curve fitting based approximation techniques for fractional-order differentiator or integrator are developed. …”
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  16. 16
    Feedforward neural network for solving particular fractional differential equations

    Feedforward neural network for solving particular fractional differential equations by Admon, Mohd Rashid

    Published 2024
    “…This research aims to develop a scheme based on a feedforward neural network (FNN) with a vectorized algorithm (FNNVA) for solving FDEs in the Caputo sense (FDEsC) using selected first-order optimization techniques: simple gradient descent (GD), momentum method (MM), and adaptive moment estimation method (Adam). …”
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  17. 17
    Solving fractional differential equations using fractional explicit method

    Solving fractional differential equations using fractional explicit method by Yip, Lian Yiung, Zanariah Abdul Majid

    Published 2024
    “…This research is focusing in solving the fractional differential equations (FDEs) for linear and non-linear type using fractional explicit method (FEM) with constant step-size. …”
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  18. 18
    Solving fractional differential equations using fractional explicit method

    Solving fractional differential equations using fractional explicit method by Yiung, Yip Lian, Abdul Majid, Zanariah

    Published 2024
    “…This research is focusing in solving the fractional differential equations (FDEs) for linear and non-linear type using fractional explicit method (FEM) with constant step-size. …”
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  19. 19
    Uncertain viscoelastic models with fractional order: a new spectral tau method to study the numerical simulations of the solution

    Uncertain viscoelastic models with fractional order: a new spectral tau method to study the numerical simulations of the solution by Ahmadian, A., Ismail, F., Salahshour, S., Baleanu, D., Ghaemi, F.

    Published 2017
    “…A new and accurate numerical algorithm using a spectral tau technique based on the generalized fractional Legendre polynomials (GFLPs) is developed to solve those problems under uncertainty. …”
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  20. 20
    A Wavelet-Based Approach For The Analytical Solutions Of Fractional Differential Equations And The Numerical Solutions Of Fractional Integral Equations

    A Wavelet-Based Approach For The Analytical Solutions Of Fractional Differential Equations And The Numerical Solutions Of Fractional Integral Equations by Loong, Marcus Ong Wei

    Published 2024
    “…Following the rise of fractional-order models and consequently, their fractional governing equations, new analytical and numerical methods have been developed and studied extensively. …”
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