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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
    Application of the Hybrid Artificial Neural Network Coupled with Rolling Mechanism and Grey Model Algorithms for Streamflow Forecasting Over Multiple Time Horizons

    Application of the Hybrid Artificial Neural Network Coupled with Rolling Mechanism and Grey Model Algorithms for Streamflow Forecasting Over Multiple Time Horizons by Yaseen, Zaher Mundher, Fu, Minglei, Wang, Chen, Mohtar, Wan Hanna Melini Wan, Deo, Ravinesh C., El-Shafie, Ahmed

    Published 2018
    “…The hybrid RMGM-ERNN was found to provide better results than the hybrid RMGM-BP model. Relatively good performance of the proposed hybrid models with a data pre-processing approach provides a successful alternative to achieve better accuracy in streamflow forecasting compared to the traditional artificial neural network approach without a data pre-processing scheme.…”
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  8. 8
    A comparative analysis of machine learning algorithms for diabetes prediction

    A comparative analysis of machine learning algorithms for diabetes prediction by Alansari, Waseem Abdulmahdi, Masnizah Mohd

    Published 2024
    “…The methodology involves data collection, pre-processing, and training the algorithms using k-fold cross-validation. …”
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  9. 9
    Data Pre Processing Methodology for Computational Experiment in Analyzing Protein Interaction Networks

    Data Pre Processing Methodology for Computational Experiment in Analyzing Protein Interaction Networks by Jamaludin, Sallim, Rosni, Abdullah, Ahamad Tajudin, Khader

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  10. 10
    ASIC Layout Design-Space Exploration of Pan-and-Tompkins Pre-Processing Algorithm for High Efficiency Electrocardiogram Monitor

    ASIC Layout Design-Space Exploration of Pan-and-Tompkins Pre-Processing Algorithm for High Efficiency Electrocardiogram Monitor by Jia, Hui Lim, Yuan, Wen Hau, Hoe, Tung Yew, Sreedharan Baskara Dass

    Published 2020
    “…Moreover, long hour ECG monitoring requires an efficient architecture to support real-time processing and low power consumption. This paper presents an application specific integrated circuit (ASIC) design of Pan-and-Tompkins ECG pre-processing algorithm which aims to remove several unwanted noise to increase analysis accuracy. …”
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  11. 11
    EEG-and MRI-based epilepsy source localization using multivariate empirical mode decomposition and inverse solution method

    EEG-and MRI-based epilepsy source localization using multivariate empirical mode decomposition and inverse solution method by Khosropanah, Pegah

    Published 2018
    “…The accuracy of ESL depends on all the stages of data processing including: head model reconstruction, signal pre-processing and inverse solution. …”
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  12. 12
    The Design of Pre-Processing Multidimensional Data Based on Component Analysis

    The Design of Pre-Processing Multidimensional Data Based on Component Analysis by Jasni, Mohamad Zain, Rahmat Widia, Sembiring

    Published 2011
    “…RapidMiner is used for data pre-processing using FastICA algorithm. Kernel K-mean is used to cluster the pre-processed data and Expectation Maximization (EM) is used to model. …”
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  13. 13
    Integration of image processing algorithm and deep learning approaches to monitor ginger plant

    Integration of image processing algorithm and deep learning approaches to monitor ginger plant by Tan, Cheng Yong

    Published 2024
    “…The image processing techniques will be used to pre-process and enhance the quality of the images to making it easier for the deep learning model to identify the ginger plants. …”
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  14. 14
    Predicting bankruptcy using ant colony optimization / Nur Syafiqah Abdul Ghani

    Predicting bankruptcy using ant colony optimization / Nur Syafiqah Abdul Ghani by Abdul Ghani, Nur Syafiqah

    Published 2021
    “…To achieve the set objectives, this research is conducted through three-phase of research activities which are Data pre-processing, Model Development, and Model Validation. …”
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  15. 15
    The effect of pre-processing techniques and optimal parameters on BPNN for data classification

    The effect of pre-processing techniques and optimal parameters on BPNN for data classification by HUSSEIN, AMEER SALEH

    Published 2015
    “…In this research, a performance analysis based on different activation functions; gradient descent and gradient descent with momentum, for training the BP algorithm with pre-processing techniques was executed. …”
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  16. 16
    Integration of image processing algorithm and deep learning approaches to monitor ginger plant

    Integration of image processing algorithm and deep learning approaches to monitor ginger plant by Tan, Cheng Yong

    Published 2024
    “…The image processing techniques will be used to pre-process and enhance the quality of the images to making it easier for the deep learning model to identify the ginger plants. …”
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  17. 17
    Adaptive Fast Orthogonal Search (FOS) algorithm for forecasting streamflow

    Adaptive Fast Orthogonal Search (FOS) algorithm for forecasting streamflow by Osman A., Afan H.A., Allawi M.F., Jaafar O., Noureldin A., Hamzah F.M., Ahmed A.N., El-shafie A.

    Published 2023
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  18. 18
    Improvement real-time detection of moving vehicle in a dynamic scene using shadow removal method / Khairul Azman Ahmad, Mohd Halim Mohd Noor,Mohamad Adha Mohamad Idin

    Improvement real-time detection of moving vehicle in a dynamic scene using shadow removal method / Khairul Azman Ahmad, Mohd Halim Mohd Noor,Mohamad Adha Mohamad Idin by Ahmad, Khairul Azman, Mohd Noor, Mohd Halim, Mohamad Idin, Mohamad Adha

    Published 2011
    “…There are four major steps in a background subtraction algorithm, which are pre-processing, background modeling, foreground detection, and data validation. …”
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  19. 19
    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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  20. 20
    M-Factors Fuzzy Time Series for Forecasting Moving Holiday Electricity Load Demand in Malaysia (S/O 14589)

    M-Factors Fuzzy Time Series for Forecasting Moving Holiday Electricity Load Demand in Malaysia (S/O 14589) by Mansor, Rosnalini, Mat Kasim, Maznah, Othman, Mahmod, Zaini, Bahtiar Jamili

    “…The modified algorithm, Weighted Subsethood Segmented Fuzzy Time Series (WeSuSFTS) consists of four main phases; data pre-processing, model development, model implementation and model evaluation. …”
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