Search Results - (( java implementation mining algorithm ) OR ( programming learning force algorithm ))

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  1. 1

    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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    Thesis
  2. 2

    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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    Article
  3. 3

    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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    Conference or Workshop Item
  4. 4

    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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    Conference or Workshop Item
  5. 5

    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
  6. 6

    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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  7. 7

    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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    Thesis
  8. 8

    Development of a software for simulating active force control schemes of a two-link planar manipulator by Mailah, Musa, Poh, Yang Liang

    Published 2005
    “…On Top Of That, The Graphical Results Can Be Observed And Analysed On-Line While The Program Is Running. By Using Matlab And Its Gui Facility, All The AFC Schemes Already Described In The Previous Works Such As The AFC With Crude Approximation Method, AFC And Iterative Learning (Afcail), AFC And Neural Network (Afcann), AFC And Fuzzy Logic (Afcafl), And AFC And Genetic Algorithm (Afcaga) Schemes Were Linked Into A Single Menu-Driven Program Where Each Of The Scheme Can Be Easily Selected And Executed By The User. …”
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    Article
  9. 9

    Machine learning model to predict the contact of angle using mineralogy, TOC and process parameters in shale by Ameenuddin Irfan, S., Fadhli, M.Z., Padmanabhan, E.

    Published 2021
    “…The application aims to develop a machine learning program using the algorithm of Support Vector Machine or Gaussian Process Regression to successfully predict the contact angle. …”
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    Conference or Workshop Item
  10. 10

    Development of a software for simulating active force control schemes of a two–link planar manipulator by Mailah, Musa, Poh, Yang Liang

    Published 2005
    “…On top of that, the graphical results can be observed and analysed on–line while the program is running. By using MATLAB and its GUI facility, all the AFC schemes already described in the previous works such as the AFC with crude approximation method, AFC and Iterative Learning (AFCAIL), AFC and Neural Network (AFCANN), AFC and Fuzzy Logic (AFCAFL), and AFC and Genetic Algorithm (AFCAGA) schemes were linked into a single menu–driven program where each of the scheme can be easily selected and executed by the user. …”
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    Article
  11. 11
  12. 12

    A review of classification techniques for electromyography signals by Mohd Saad, Norhashimah, Omar, Siti Nashayu, Abdullah, Abdul Rahim, Shair, Ezreen Farina, H.Rashid

    Published 2023
    “…Machine Learning (ML) is an area of Artificial Intelligent (AI) with a concept that a computer program can learn and familiarize to new data without human intervention. …”
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  13. 13
  14. 14

    Multistage quality control in manufacturing process using blockchain with machine learning technique by Gu, J., Zhao, L., Yue, X., Arshad, N.I., Mohamad, U.H.

    Published 2023
    “…To this goal, a variety of machine learning algorithms are being studied. Data protection and monitoring is also another concern that is a critical component of the organization. …”
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  15. 15

    Analyzing surface settlement factors in single and twin tunnels : A review study by Huat, Chia Yu, Danial Jahed, Armaghani, Lai, Sai Hin, Hossein, Motaghedi, Panagiotis G., Asteris, Pouyan, Fakharin

    Published 2024
    “…Practical implications for practicing engineers include thorough site investigations, risk assessments and comprehensive monitoring programs. Leveraging historical data and ML algorithms can enhance SS prediction accuracy and aid in proactive risk management. …”
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  16. 16

    Validation of deep convolutional neural network for age estimation in children using mandibular premolars on digital panoramic dental imaging / Norhasmira Mohammad by Mohammad, Norhasmira

    Published 2022
    “…The semi-automated dental staging system developed in this study is based on the Malay children’s population and uses a brain-inspired learning algorithm termed "deep learning". The methodology is comprised of four major steps: image preprocessing, which adheres to the inclusion criteria for panoramic dental radiographs, segmentation, and classification of mandibular premolars according to Demirjian's staging system using the Dynamic Programming-Active Contour (DP-AC) method and Deep Convolutional Neural Network (DCNN), respectively, and statistical analysis. …”
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    Thesis
  17. 17

    A Confined Workforce Planning Model with Plugging for Service Organizations Using Network Flow Under Finite Horizon, Varying Demand Senario by Varughese, T. C.

    Published 2015
    “…The scope of the study is limited to finite planning horizon. Also, employee-learning through experience is not considered in this study. …”
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    Thesis