Search Results - (( based interpolation learning 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
    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
    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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  7. 7
    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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  8. 8
    Prediction of rice biomass using machine learning algorithms

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

    Published 2022
    “…Unmanned aerial vehicles (UAVs) may address these issues. Machine learning algorithms (MLs) can predict rice biomass from UAV-based vegetation indices (VIs). …”
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  9. 9
    Adaptive GRNN for the modelling of dynamic plants

    Adaptive GRNN for the modelling of dynamic plants by Yusof, Rubiyah, Khalid, Marzuki, Teo, Lian Seng

    Published 2002
    “…These adaptation strategies are formulated based on the inherent advantageous features found in GRNN, such as highly localised pattern nodes, good interpolation capability, instantaneous learning, etc.. …”
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  10. 10
    Mortality Trends and Its Impact on the Pension Liabilities

    Mortality Trends and Its Impact on the Pension Liabilities by Rose Irnawaty Ibrahim

    Published 2025
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  11. 11
    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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  12. 12
    Small target detection of Unmanned Aerial Vehicles based on GDWNet in the digital economy

    Small target detection of Unmanned Aerial Vehicles based on GDWNet in the digital economy by Zhang, Yan, Zhang, Jing, Mustaffa, Mas Rina

    Published 2025
    “…During the feature fusion stage, DySample is employed to generate content-aware offsets through learning. This approach effectively breaks the fixed interpolation rules of traditional upsampling methods, enabling more dynamic, flexible, and semantically rich upsampling of the input feature maps, thereby improving the quality of feature integration. …”
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  13. 13
    Kaedah Kolorimetri untuk Analisis Kuantitatif Kapsaisin Secara Pencaman Corak Menggunakan Jaringan Neural Tiruan

    Kaedah Kolorimetri untuk Analisis Kuantitatif Kapsaisin Secara Pencaman Corak Menggunakan Jaringan Neural Tiruan by Mat Arip, Mohamad Nasir, Ahmad, Musa, Mokhtar, Ahmed Mahir, Taib, Mohd. Nasir, Heng, Lee Yook

    Published 2002
    “…A three layer feed-forward neural network was used and network training was performed by using back propagation algorithm. For the determination of capsaicin, a neural network with 20 hidden neurons, 0.00001% learning rate and trained over 47,738 cycles produced the best result. …”
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  14. 14
    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. In the case of 3D study of pole - dipole data, the gradient descent with momentum and an adaptive learning rate algorithm is found to be the most efficient paradigm. …”
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  15. 15
    Malware Detection using Deep Learning (DL)

    Malware Detection using Deep Learning (DL) by Chowdhury Sajadul Islam, Madihah Mohd Saudi, Nur Hafiza Zakaria, Muji Setiyo

    Published 2024
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  16. 16
    ReSTiNet : On improving the performance of Tiny-YOLO-Based CNN architecture for applications in human detection

    ReSTiNet : On improving the performance of Tiny-YOLO-Based CNN architecture for applications in human detection by Sumit, Shahriar Shakir, Awang Rambli, Dayang Rohaya, Mirjalili, Seyedali, Ejaz, Muhammad Mudassir, Miah, Md Saef Ullah

    Published 2022
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