Search Results - (( java application mining algorithm ) OR ( pattern evaluation based 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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    Final Year Project / Dissertation / Thesis
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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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    Citation Index Journal
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  7. 7
    A modified fuzzy min-max neural network with a genetic-algorithm-based rule extractor for pattern classification

    A modified fuzzy min-max neural network with a genetic-algorithm-based rule extractor for pattern classification by Quteishat, A., Lim, C.P., Tan, K.S.

    Published 2010
    “…The first stage consists of a modified fuzzy min-max (FMM) neural-network-based pattern classifier, while the second stage consists of a genetic-algorithm (GA)-based rule extractor. …”
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  8. 8
    IncSPADE: An Incremental Sequential Pattern Mining Algorithm Based on SPADE Property

    IncSPADE: An Incremental Sequential Pattern Mining Algorithm Based on SPADE Property by Omer, Adam, Zailani, Abdullah, Amir, Ngah, Kasypi, Mokhtar, Wan Muhamad Amir, Wan Ahmad, Herawan, Tutut, Noraziah, Ahmad, Mustafa, Mat Deris, Abdul Razak, Hamdan

    Published 2016
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  9. 9
    An expanded square pattern technique in swarm of quadcopters for exploration algorithm

    An expanded square pattern technique in swarm of quadcopters for exploration algorithm by Zuhri, Muhammad Fuad Reza, Ismail, Amelia Ritahani

    Published 2017
    “…We simulate the swarm-based exploration algorithm with expanded square pattern using a VREP simulator. …”
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  10. 10
    Clustering ensemble learning method based on incremental genetic algorithms

    Clustering ensemble learning method based on incremental genetic algorithms by Ghaemi, Reza

    Published 2012
    “…In the first and second phases, a threshold fuzzy c-means clustering algorithm as a clusterer and a pattern ensemble learning method based on the incremental genetic-based algorithms are proposed respectively. …”
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  11. 11
    Text searching algorithm using boyer moore horspool (BMH) algorithm

    Text searching algorithm using boyer moore horspool (BMH) algorithm by Siti Nurafiqah, Jaafar

    Published 2015
    “…Based on the study, the average analysis result for this algorithm is 93% which is a strong match.…”
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    Undergraduates Project Papers
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  12. 12
    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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  13. 13
    Variable block based motion estimation using hexagon diamond full search algorithm (HDFSA) via block subtraction technique

    Variable block based motion estimation using hexagon diamond full search algorithm (HDFSA) via block subtraction technique by Hardev Singh, Jitvinder Dev Singh

    Published 2015
    “…In the video and frame selection, pre-defined video which have different type of motion and size is used for the algorithm evaluation purpose. The threshold calculation is based on the video selected. …”
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  14. 14
    Statistical computing for forensic firearm pattern identification: Evaluating a fisher linear discriminant analysis-based algorithm against fixed-impulse noise

    Statistical computing for forensic firearm pattern identification: Evaluating a fisher linear discriminant analysis-based algorithm against fixed-impulse noise by Chuan, Zun Liang, Abraham Lim, Bing Sern, Tan, Chek Cheng, Abdul Aziz, Jemain, Liong, Choong-Yeun

    Published 2025
    “…This study evaluates the robustness of the FLDA-based ballistic identification algorithm against fixed-value impulse noise, including pepper, salt, and salt-and-pepper noise. …”
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  15. 15
    Development of a new robust hybrid automata algorithm based on surface electromyography (SEMG) signal for instrumented wheelchair control

    Development of a new robust hybrid automata algorithm based on surface electromyography (SEMG) signal for instrumented wheelchair control by Mohd Hanafi, Muhammad Sidik

    Published 2020
    “…Addition of hybrid automata algorithm to run pattern and non-pattern recognition based control methods is an advantage to increase accuracy in differentiating forward stroke or hand return activity. …”
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  16. 16
    Realization Of The 1D Local Binary Pattern (LBP) Algorithm In Raspberry Pi For Iris Classification Using K-NN Classifier

    Realization Of The 1D Local Binary Pattern (LBP) Algorithm In Raspberry Pi For Iris Classification Using K-NN Classifier by Siow, Shien Loong

    Published 2018
    “…Secondly, the K-NN classifier is used to classify the 1D-LBP based features from the first stage. There are two methods to evaluate the features, which are one versus one and one versus many. …”
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    Monograph
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  17. 17
    Prime-based method for interactive mining of frequent patterns

    Prime-based method for interactive mining of frequent patterns by Nadimi-Shahraki, Mohammad-Hossein

    Published 2010
    “…Over the past decade, an increasing number of efficient mining algorithms have been proposed to mine the frequent patterns by satisfying a user specified threshold called minimum support (minsup). …”
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  18. 18
    The development of an automated pattern recognition based on neural network / Irni Hamiza Hamzah, Mohammad Nizam Ibrahim and Linda Mohd Kasim

    The development of an automated pattern recognition based on neural network / Irni Hamiza Hamzah, Mohammad Nizam Ibrahim and Linda Mohd Kasim by Hamzah, Irni Hamiza, Ibrahim, Mohammad Nizam, Mohd Kasim, Linda

    Published 2006
    “…Based on this idea, the objective of this project is to develop an automated pattern recognition system based on neural network to recognize the pattern of loaded data file. …”
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    Research Reports
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  19. 19
    Linear-PSO with binary search algorithm for DNA Motif Discovery / Hazaruddin Harun

    Linear-PSO with binary search algorithm for DNA Motif Discovery / Hazaruddin Harun by Harun, Hazaruddin

    Published 2015
    “…Evaluation of these algorithms showed that the results are unsatisfactory due to the lower validity and accuracy of these algorithms. …”
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  20. 20
    An improved fast scanning algorithm based on distance measure and threshold function in region image segmentation

    An improved fast scanning algorithm based on distance measure and threshold function in region image segmentation by Ismael, Ahmed Naser

    Published 2016
    “…Hence, this study proposes an Improved Fast Scanning algorithm that is based on Sorensen distance measure and adaptive threshold function. …”
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