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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
    Loss reduction in distribution networks using new network reconfiguration algorithm

    Loss reduction in distribution networks using new network reconfiguration algorithm by Kashem, M.A., Moghavvemi, M., Mohamed, A., Jasmon, G.B.

    Published 1996
    “…For this purpose a simple-to-use formula, called loop loss reduction formula, has been developed. …”
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  9. 9
    Comparative analysis of sine cosine and social network search-based algorithm for software test redundancy reduction optimization

    Comparative analysis of sine cosine and social network search-based algorithm for software test redundancy reduction optimization by Mekeng, Ambros Magnus Rudolf, Kamal Z., Zamli, Muhammad Zarlis, .

    Published 2024
    “…Addressing this issue as an optimization problem, many existing works adopts metaheuristic algorithms to eliminate redundancy. Acknowledging the fact that no single metaheuristic algorithm is superior than its counterparts as well as taking the opportunity to adopt recent algorithm, our work present a comparative study (i.e., solving the TRR problem) using two recently developed metaheuristic algorithms namely the Social Network Search Algorithm (SNS) and the Sine Cosine Algorithm (SCA). …”
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  10. 10
    Parallelization of noise reduction algorithm for seismic data on a beowulf cluster

    Parallelization of noise reduction algorithm for seismic data on a beowulf cluster by Aziz, I. A., Sandran, T., Haron, N. S., Hasan, M. H, Mehat, M.

    Published 2010
    “…The parallel algorithm was developed using C language with the utilization of the Message Passing Interface (MPI) library. …”
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  11. 11
    Development of CT Metal Artifact Reduction Algorithm for use in Radiotherapy Treatment Planning System

    Development of CT Metal Artifact Reduction Algorithm for use in Radiotherapy Treatment Planning System by Abdul Aziz, Mohd Zahri, Osman, Noor Diyana, Salikin, Md Saion, Yusoff, A.L.

    Published 2011
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  12. 12
    Loss reduction in distribution networks by network reconfiguration: a two stage solution approach

    Loss reduction in distribution networks by network reconfiguration: a two stage solution approach by Nallagownden, Perumal

    Published 2004
    “…For this purpose a simple-to-use formula, called loop loss reduction formula has been developed. …”
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  13. 13
    Active intelligent control of vibration of flexible plate structures

    Active intelligent control of vibration of flexible plate structures by Md Salleh, Salihatun

    Published 2011
    “…Tests with various disturbance signals show that good vibration reduction is achieved with the developed model-based SISO-AVC algorithms. …”
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  14. 14
    Performance of various forecasting algorithms to reduce the number of transmitted packets by sensor node in wireless sensor networks

    Performance of various forecasting algorithms to reduce the number of transmitted packets by sensor node in wireless sensor networks by Husni, Muhammed Ihsan

    Published 2018
    “…The selected algorithms for the reduction algorithm in the transmissions include Move Average algorithm (MA), Autoregressive all-pole model parameters — Burg’s algorithm. …”
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  15. 15
    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction

    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama A

    Published 2022
    “…The results show that using dimensionality reduction techniques along with the ML algorithms with a dataset containing high-dimensional data significantly improves the classification results. …”
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  16. 16
    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction

    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama A.

    Published 2022
    “…The results show that using dimensionality reduction techniques along with the ML algorithms with a dataset containing high-dimensional data significantly improves the classification results. …”
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  17. 17
    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction

    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Ahmed Dheyab, Saad, Mohammed Abdulameer, Shaymaa, Mostafa, Salama A

    Published 2022
    “…The results show that using dimensionality reduction techniques along with the ML algorithms with a dataset containing high-dimensional data significantly improves the classification results. …”
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  18. 18
    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction

    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama

    Published 2022
    “…The results show that using dimensionality reduction techniques along with the ML algorithms with a dataset containing high-dimensional data significantly improves the classification results. …”
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  19. 19
    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction

    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama

    Published 2023
    “…The results show that using dimensionality reduction techniques along with the ML algorithms with a dataset containing high-dimensional data significantly improves the classification results. …”
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  20. 20
    Numerical Integration And Data Reduction For Application In Photometry

    Numerical Integration And Data Reduction For Application In Photometry by Chew, Tong Fatt

    Published 2003
    “…The first derivatives at the interior knots are estimated from the average of the angles subtended to the horizontal by two adjacent slopes. In a further development, the algorithm is extended to create another algorithm using quintic polynomial interpolation that has C2 continuity, providing smoother interpolation curves but retaining the local nature of interpolation.…”
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