Search Results - (( java implementation mining algorithm ) OR ( using control chart 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
    “…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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  2. 2
    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
    “…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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  3. 3
    Scalable approach for mining association rules from structured XML data

    Scalable approach for mining association rules from structured XML data by Abazeed, Ashraf Riad, Mamat, Ali, Sulaiman, Md. Nasir, Ibrahim, Hamidah

    Published 2009
    “…Many techniques have been proposed to tackle the problem of mining XML data we study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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  4. 4
    Mining association rules from structured XML data

    Mining association rules from structured XML data by Abazeed, Ashraf Riad, Mamat, Ali, Sulaiman, Md. Nasir, Ibrahim, Hamidah

    Published 2009
    “…Many techniques have been proposed to tackle the problem of mining XML data. We study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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  5. 5
    ROAD algorithm for control charts / Gejza Dohnal

    ROAD algorithm for control charts / Gejza Dohnal by Dohnal, Gejza

    Published 2015
    “…Using with robust control chart we obtain a robust adaptive control chart (ROAD). …”
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  6. 6
    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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  7. 7
    Construction of fuzzy control charts by using triangular and gaussian fuzzy numbers for solder paste thickness

    Construction of fuzzy control charts by using triangular and gaussian fuzzy numbers for solder paste thickness by Ahmad Basri, Nur Ain Zafirah

    Published 2018
    “…This study aims to generate fuzzy numbers by using triangular and Gaussian approaches and to analyse the algorithm of fuzzy control charts by using α-cut and to analyse the algorithm of traditional control charts of -R and -S towards the solder paste thickness of integrated circuit data. …”
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  8. 8
    Fiducial registration error as a statistical process control metric in image-guidance radiotherapy with fiducial markers

    Fiducial registration error as a statistical process control metric in image-guidance radiotherapy with fiducial markers by Ung, N.M., Wee, L.

    Published 2011
    “…A procedure for estimating control parameters of a SPC control chart (x-chart) from a small number of initial observations (N) of FRE was implemented. …”
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  9. 9
    Development of fault detection, diagnosis and control system identification using multivariate statistical process control (MSPC)

    Development of fault detection, diagnosis and control system identification using multivariate statistical process control (MSPC) by Ibrahim, Kamarul 'Asri, Ahmad, Arshad, Ali, Mohamad Wijayanuddin, Mak, Weng Yee

    Published 2006
    “…Shewhart Control Chart (SCC) and Range Control Chart (RCC) are used with the developed correlation coefficients for FDD. …”
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    Monograph
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  10. 10
    Development Of Two New Auxiliary Information Control Charts, And Economic And Economic-Statistical Designs Of Several Auxiliary Information Control Charts

    Development Of Two New Auxiliary Information Control Charts, And Economic And Economic-Statistical Designs Of Several Auxiliary Information Control Charts by Ng Peh, Sang

    Published 2020
    “…The use of auxiliary information (AI) concept in control charts is receiving increasing attention among researchers. …”
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  11. 11
    Image clustering comparison of two color segmentation techniques

    Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

    Published 2010
    “…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. …”
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  12. 12
    Fast and Accuracy Control Chart Pattern Recognition using a New cluster-k-Nearest Neighbor

    Fast and Accuracy Control Chart Pattern Recognition using a New cluster-k-Nearest Neighbor by Brahim Belhaouari, samir

    Published 2009
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    Citation Index Journal
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  13. 13
    Fast and Accuracy Control Chart Pattern Recognition using a New cluster-k-Nearest Neighbor

    Fast and Accuracy Control Chart Pattern Recognition using a New cluster-k-Nearest Neighbor by Brahim Belhaouari, samir

    Published 2008
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  14. 14
    Improving the synthetic coefficient of variation chart by incorporating side sensitivity

    Improving the synthetic coefficient of variation chart by incorporating side sensitivity by Lee, PingYin

    Published 2024
    “…The control chart is recognized as a crucial technique in Statistical Process Control. …”
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  15. 15
    Computer control of batch process plant (software development)

    Computer control of batch process plant (software development) by Safian, Salehudin

    Published 1995
    “…The algorithm has been successful tested using the Non-interacting Liquid Level Control of Three lank System plant models transfer function.…”
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  16. 16
    Fault diagnostic advisory system using moving-range chart and hazard operability study.

    Fault diagnostic advisory system using moving-range chart and hazard operability study. by Heng, Han Yann, Ali, Mohamad Wijayanuddin, Kamsah, Mohd Zaki

    Published 2007
    “…Firstly, a plant model was simulated by using commercial HYSYS. PlantTM stimulator. Moving-Range (x-MR) Chart and (HAZOP) study were used to define the causes and consequences of process deviation based on selected parameter for each study node. …”
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  17. 17
    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
    “…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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  18. 18
    Fault diagnostic advisory system using moving-range chart and hazard operability study

    Fault diagnostic advisory system using moving-range chart and hazard operability study by Heng, Han Yann, Ali, Mohamed Wijayanuddin, Kamsah, Mohd. Zaki

    Published 2007
    “…Firstly, a plant model was simulated by using commercial HYSYS. PlantTM simulator. Moving-Range (x-MR) Chart and HAZOP study were used to define the causes and consequences of process deviation based on selected parameter for each study node. …”
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  19. 19
    Monitoring the coefficient of variation using a variable sample size EWMA chart

    Monitoring the coefficient of variation using a variable sample size EWMA chart by Muhammad, Anis Nabila, Yeong, Wai Chung, Chong, Zhi Lin, Lim, Sok Li, Khoo, Michael Boon Chong

    Published 2018
    “…Subsequently, an optimization algorithm to optimize the performance of the proposed chart is developed. …”
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  20. 20
    Ensemble Classifier for Recognition of Small Variation in X-Bar Control Chart Patterns

    Ensemble Classifier for Recognition of Small Variation in X-Bar Control Chart Patterns by Alwan, Waseem, Ngadiman, Nor Hasrul Akhmal, Hassan, Adnan, Saufi, Syahril Ramadhan, Mahmood, Salwa

    Published 2023
    “…This study provides an improved control chart pattern recognition (CCPR) method focusing on X-bar chart patterns of small process variations using an ensemble classifier comprised of five complementing algorithms: decision tree, artificial neural network, linear support vector machine, Gaussian support vector machine, and k-nearest neighbours. …”
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