Search Results - (( developing integration collocation algorithm ) OR ( java application tree algorithm ))*

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  1. 1
    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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  2. 2
    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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  3. 3
    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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  4. 4
    Optimization in active vibration control: virtual experimentation using COMSOL multiphysics - MATLAB integration

    Optimization in active vibration control: virtual experimentation using COMSOL multiphysics - MATLAB integration by Md Nor, Khairul Affendy, Abdul Muthalif, Asan Gani, Wahid, Azni N.

    Published 2014
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  5. 5
    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
    “…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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  6. 6
    Neural network algorithm-based fall detection modelling

    Neural network algorithm-based fall detection modelling by Mohd Yusoff, Ainul Husna, Koh, Cheng Zhi, Ngadimon, Khairulnizam, Md Salleh, Salihatun

    Published 2020
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  7. 7
    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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    Citation Index Journal
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  8. 8
    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde

    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

    Published 2022
    “…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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  9. 9
    Cloudlet deployment and task offloading in mobile edge computing using variable-length whale and differential evolution optimization and analytical hierarchical process for decision-making

    Cloudlet deployment and task offloading in mobile edge computing using variable-length whale and differential evolution optimization and analytical hierarchical process for decisio... by Daba, Layth Muwafaq Abdulhussein

    Published 2023
    “…Comparing this developed algorithm with other algorithms shows its superiority in multi-objective optimization (MOO) evaluation metrics. …”
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  10. 10
    Mining Sequential Patterns Using I-PrefixSpan

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

    Published 2007
    “…In this paper, we propose an improvement of pattern growth-based PrefixSpan algorithm, called I-PrefixSpan. The general idea of I-PrefixSpan is to use the efficient data structure for general tree-like framework and separator database to reduce the execution time and memory usage. …”
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  11. 11
    AI powered asthma prediction towards treatment formulation: an android app approach

    AI powered asthma prediction towards treatment formulation: an android app approach by Murad, Saydul Akbar, Adhikary, Apurba, Md Muzahid, Abu Jafar, Sarker, Md Murad Hossain, Khan, Md. Ashikur Rahman, Hossain, Md. Bipul, Bairagi, Anupam Kumar, Masud, Mehedi, Kowsher, Md

    Published 2022
    “…We utilized eight robust machine learning algorithms to analyze this dataset. We found that the Decision tree classifier had the best performance, out of the eight algorithms, with an accuracy of 87%. …”
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  12. 12
    AI powered asthma prediction towards treatment formulation : An android app approach

    AI powered asthma prediction towards treatment formulation : An android app approach by Murad, Saydul Akbar, Adhikary, Apurba, Muzahid, Abu Jafar Md, Sarker, Md. Murad Hossain, Khan, Md. Ashikur Rahman, Hossain, Md. Bipul, Bairagi, Anupam Kumar, Masud, Mehedi, Kowsher, Md.

    Published 2022
    “…We utilized eight robust machine learning algorithms to analyze this dataset. We found that the Decision tree classifier had the best performance, out of the eight algorithms, with an accuracy of 87%. …”
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  13. 13
    A Film-Pore-Surface Concentration Dependent Model For Adsorption Of Dye Onto Activated Carbon

    A Film-Pore-Surface Concentration Dependent Model For Adsorption Of Dye Onto Activated Carbon by Choong, Thomas S. Y., Chuah, T. G., Idris, Azni, Lai, Y. L., Quek, S. Y.

    Published 2005
    “…The Governing Partial Differential Equations (Pdes) Were Transformed To Ordinary Differential Equations (Odes) Using Orthogonal Collocation (OC) Method. This Set Of Odes Was Then Integrated Using The Numerical Algorithm DIVPAG (IMSL Library Subroutine), Which Was Based On Gear’s Method. …”
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  14. 14
    Modelling of Adsorption of Dyes from Aqueous Solution by Activated Carbon

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

    Published 2004
    “…In this study, a mathematical model for adsorption rate is developed based on the FPCDSD model. The governing partial differential equations (PDEs) are transformed to ordinary differential equations (ODEs) using orthogonal collocation (OC) method. …”
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