Search Results - (( java implementation clustering algorithm ) OR ( parameter equation modeling algorithm ))

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  1. 1

    Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

    Published 2019
    “…This project will use fuzzy k-means clustering algorithm to cluster the data because it is easy to implement and have many advantages. …”
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    Thesis
  2. 2

    Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

    Published 2010
    “…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. …”
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    Thesis
  3. 3

    A Toolkit for Simulation of Desktop Grid Environment by FOROUSHAN, PAYAM CHINI

    Published 2014
    “…A simulator for desktop grid environment has been developed using Java as the implementation language due to its wide popularity. …”
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    Final Year Project
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    A web-based implementation of k-means algorithms by Lee, Quan

    Published 2022
    “…Firstly, k-luster could incorporate additional clustering algorithms, or even classification algorithms in the future. …”
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    Final Year Project / Dissertation / Thesis
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    Numerical Investigations of Nano-fluid Flow in Square Porous Cavity: Buongiorno�s Mathematical Model by Zafar, M., Sakidin, H., Dzulkarnain, I., Afzal, F.

    Published 2021
    “…The governing system of partial differential equations was discretized using the finite volume method (FVM), the continuity and momentum equations were discretized using the SIMPLE algorithm, and the generated algebraic equations are solved iteratively. …”
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    Conference or Workshop Item
  8. 8

    Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform by Alias, Norma, Satam, Noriza, Abd. Ghaffar, Zarith Safiza, Darwis, Roziha, Hamzah, Norhafiza, Islam, Md. Rajibul

    Published 2009
    “…The development of this architecture is based on several programming language as it involves algorithm implementation on C, parallelization using Parallel Virtual Machine (PVM) and Java for web services development. …”
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    Conference or Workshop Item
  9. 9

    Rock brittleness prediction through two optimization algorithms namely particle swarm optimization and imperialism competitive algorithm by Hussain, Azham, Surendar, A., Clementking, A., Kanagarajan, Sujith, Ilyashenko, Lubov K.

    Published 2018
    “…In the modeling of the predictive models, 79 datasets are used, so that Schmidt hammer rebound number, wave velocity, density, and Point Load Index (Is50) are selected as the independent (input) parameters and the BI values are considered as the dependent (output) parameter. …”
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    Article
  10. 10

    Evaluation of new rotor angle deviation regulator for synchronous generator using nonlinear swing equation by Mohamad Murad, Nor Syaza Farhana

    Published 2024
    “…Nonlinear parameters are included in the modeling, and hence the synchronous generator is portrayed as a nonlinear swing equation. …”
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    Thesis
  11. 11

    Parameter Estimation Using Improved Differential Evolution And Bacterial Foraging Algorithms To Model Tyrosine Production In Mus Musculus(Mouse) by Jia, Xing Yeoh, Chuii, Khim Chong, Mohd Saberi, Mohamad, Yee, Wen Choon, Lian, En Chai, Safaai, Deris, Zuwairie, Ibrahim

    Published 2015
    “…Global optimisation is a method to identify the optimal kinetic parameter in ordinary differential equation. From the ordinary parameter of biomathematical field, there are many unknown parameters, and commonly, the parameter is in nonlinear form. …”
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    Article
  12. 12

    Standard equations for predicting the discharge coefficient of a modified high-performance side weir by Zaji, Amir Hossein, Bonakdari, Hossein, Shamshirband, Shahaboddin

    Published 2017
    “…The Particle Swarm Optimization (PSO) algorithm was used to optimize the parameters of the equations. …”
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    Article
  13. 13

    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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    Article
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    Peak pressure analysis of foot plantar distribution based on image processing algorithm by Sabry, Ali Hussein

    Published 2018
    “…Seven levels of pressure have been successfully classified via image processing capabilities to simplify the creation of three modeling equations; polynomial, 3rd order, 5th, and 1st order equations to model each of the human body weight, foot size, and the age respectively. …”
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    Thesis
  16. 16

    Identifying and estimating solar cell parameters using an enhanced slime mould algorithm by Logeswaary, Devarajah, Mohd Ashraf, Ahmad, Jui, Julakha Jahan

    Published 2024
    “…This study proposed an enhanced slime mould algorithm (ESMA) for identifying the solar cells’ parameters for five photovoltaic (PV) models, making two modifications to the original slime mould algorithm (SMA). …”
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    Article
  17. 17

    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
    “…In conclusion, hybrid DNN with the K-Means Clustering Algorithm is proven to resolve parameter estimations of the chaotic system by developing an accurate prediction model.…”
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    Thesis
  18. 18

    Large-scale kinetic parameters estimation of metabolic model of escherichia coli by Azrag, M. A. K., Tuty Asmawaty, Abdul Kadir, Kabir, M. Nomani, Jaber, Aqeel S.

    Published 2019
    “…However, in the development of the metabolic model, large-scale kinetic parameters affect the model response if the parameter values are not assigned accurately, which, in turn, propagates the errors in the ordinary differential equations (ODEs) – the mass balance equations associated with the model. …”
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    Article
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    PSO and Linear LS for parameter estimation of NARMAX/NARMA/NARX models for non-linear data / Siti Muniroh Abdullah by Abdullah, Siti Muniroh

    Published 2017
    “…The parameter estimation step is concerned with the estimation of model parameters once the structure is known. …”
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    Thesis