Search Results - (( linear interpolating data algorithm ) OR ( java application mining algorithm ))

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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
    STEP-NC Interpolator for General 2D and 3D Parametric Curve / Dzullijah Ibrahim...[et al.]

    STEP-NC Interpolator for General 2D and 3D Parametric Curve / Dzullijah Ibrahim...[et al.] by Ibrahim, Dzullijah, Yaakob, Yusli, Hussin, Norasikin, Samad, Zahurin

    Published 2017
    “…The generated output of the interpolated data is computer simulated for 2D circular-arc paths and 3D linear paths to verify the validity of the interpolator input generated by the proposed interface.…”
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  4. 4
    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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  5. 5
    The development of spatio-temporal data model for dynamic visualization of virtual geographical information system

    The development of spatio-temporal data model for dynamic visualization of virtual geographical information system by Mohd. Rahim, Mohd. Shafry, Daman, Daut

    Published 2006
    “…Result shows that the proposed data model is able to perform well with a visualization algorithm using linear interpolation and an improved TIN structure. …”
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    Monograph
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  6. 6
    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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  7. 7
    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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    Final Year Project / Dissertation / Thesis
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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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    Citation Index Journal
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  9. 9
    Assessment of landsat 7 scan line corrector-off data gap-filling methods for seagrass distribution mapping

    Assessment of landsat 7 scan line corrector-off data gap-filling methods for seagrass distribution mapping by Hossain, Mohammad Shawkat, Bujang, Japar Sidik, Zakaria @ Ya, Muta Harah, Hashim, Mazlan

    Published 2015
    “…To assess the geometric and radiometric fidelity of the recovered pixels, three potential gap-filling methods were examined: (a) geostatistical neighbourhood similar pixel interpolator (GNSPI); (b) weighted linear regression (WLR) algorithm integrated with the Laplacian prior regularization method; and (c) the local linear histogram matching method. …”
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  10. 10
    Pemetaan Pm10 Dan Aot Menggunakan Teknik Penderiaan Jauh Di Semenanjung Malaysia

    Pemetaan Pm10 Dan Aot Menggunakan Teknik Penderiaan Jauh Di Semenanjung Malaysia by San, Limhwee

    Published 2006
    “…The developed algorithms are two-band algorithm, terma linear and modified algorithm from the combination of the visible and infrared thermal bands. …”
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  11. 11
    Features selection for intrusion detection system using hybridize PSO-SVM

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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  12. 12
    Volumetric spatiotemporal data model

    Volumetric spatiotemporal data model by Mohd. Rahim, Mohd. Shafry, Mohamaed Shariff, Abdul Rashid, Alias, Mohammad Ashari

    Published 2007
    “…Result shows that the data model which has been proposed can work with a visualization algorithm using linear interpolation and improvement TIN structure.…”
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  13. 13
    Inversion of 2D and 3D DC resistivity imaging data for high contrast geophysical regions using artificial neural networks / Ahmad Neyamadpour

    Inversion of 2D and 3D DC resistivity imaging data for high contrast geophysical regions using artificial neural networks / Ahmad Neyamadpour by Neyamadpour, Ahmad

    Published 2010
    “…These results show that,for all the arrays (2D and 3D) except 3D pole - dipole data, resilient propagation is the most efficient algorithm for training the DC resistivity data. …”
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  14. 14
    S-box construction from non-permutation power functions

    S-box construction from non-permutation power functions by Isa H., Jamil N., Z'aba M.R.

    Published 2023
    Conference paper
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  15. 15
    Development and Application of a Finite Element Distributed Rainfall Runoff Simulation Model

    Development and Application of a Finite Element Distributed Rainfall Runoff Simulation Model by Huang, Yuk Feng

    Published 2000
    “…Finite element simulations have been shown to compare favourably with observed laboratory data. Linear element simulation was found to give results as accurate as the quadratic element simulation. …”
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  16. 16
    Parallel strategies on a distributed parallel computer system

    Parallel strategies on a distributed parallel computer system by Alias, Norma

    Published 2004
    “…There are IADEI method which is based on Richardson's formula and AGE\_BRIAN which is based on linear interpolation concept. The development of a few strategies parallel is being as a mechanism for IADE to make it implemented in parallel. …”
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  17. 17
    Cause and effect prediction in manufacturing process using an improved neural networks

    Cause and effect prediction in manufacturing process using an improved neural networks by Mohd Nawi, Nazri, Abdul Hamid, Noorhamreeza, Samsudin, Noor Azah, Harun, Zawati, Ab Aziz, Mohd Firdaus, Ramli, Azizul Azhar

    Published 2017
    “…A new approach to enhance the performance of the current Knowledge Hyper-surface method has been proposed by constructing midpoints between each primary weight along each dimension by using a quadratic Lagrange interpolation polynomial. The new secondary-weight values, generated due to the addition of midpoints, were also represented as a linear combination of the corresponding primary/axial weight values. …”
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  18. 18
    Prediction of rice biomass using machine learning algorithms

    Prediction of rice biomass using machine learning algorithms by Radhwane, Derraz

    Published 2022
    “…Further, the Q-TESI, C-TESI, and LTESI minimise the proportionality of interpolation error to the square of the distance between the data points compared to the LN-TESI. …”
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  19. 19
    Ensemble learning using multi-objective optimisation for arabic handwritten words

    Ensemble learning using multi-objective optimisation for arabic handwritten words by Ghadhban, Haitham Qutaiba

    Published 2021
    “…Most ensemble learning approaches are based on the assumption of linear combination, which is not valid due to differences in data types. …”
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  20. 20
    Development of mapping methods for seagrass meadows in Malaysia by using landsat images

    Development of mapping methods for seagrass meadows in Malaysia by using landsat images by Hossain, Mohammad Shawkat

    Published 2015
    “…The next study was focused on assessment of the geometric and radiometric fidelity of images reconstructed by three potential gap-filling methods: (1) Geostatistical Neighbourhood Similar Pixel Interpolator (GNSPI), (2) Weighted linear regression algorithm integrated with Laplacian prior regularization, and (3) Local Linear Histogram Matching methods. …”
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