Search Results - (( java implementation tree algorithm ) OR ( pattern grading patterns algorithm ))

  • Showing 1 - 17 results of 17
Refine Results
  1. 1
  2. 2
  3. 3

    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”. …”
    Get full text
    Get full text
    Get full text
    Article
  4. 4
  5. 5

    Predicting building damage grade by earthquake: a Bayesian Optimization-based comparative study of machine learning algorithms by Al-Rawashdeh, Mohammad, Al Nawaiseh, Moh’d, Yousef, Isam, Bisharah, Majdi, Alkhadrawi, Sajeda, Al-Bdour, Hamza

    Published 2024
    “…The optimized models classified building damage grades with an AUROC of 0.9952. Comparing machine learning algorithms yields insights. …”
    Get full text
    Get full text
    Article
  6. 6

    MELODY TRAINING WITH SEGMENT-BASED TILT CONTOUR FOR QURANIC TARANNUM by Hanum, H.M., Abas, L.H.M., Aziz, A.S., Bakar, Z.A., Diah, N.M., Ahmad, W.F.W., Ali, N.M., Zamin, N.

    Published 2021
    “…The proposed application also provides feedback in the form of a grade and a percentage of accuracy, as determined by a melody curve similarity algorithm. …”
    Get full text
    Get full text
    Article
  7. 7

    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

    Published 2022
    “…The method was implemented using Java and the results of the simulation were evaluated using five standard performance metrics: accuracy, AUC, precision, recall, and f-Measure. …”
    Get full text
    Get full text
    Get full text
    Thesis
  8. 8

    Classification of compressive strength grades for lightweight aggregate concrete with palm oil fuel ash (POFA) using k-Nearest Neighbour (k-NN) by Mohamad Hushnie, Haron, Nur Azzimah, Zamri, Khairunisa, Muthusamy

    Published 2023
    “…Next, the grades of concrete were classified using a machine learning algorithm named k-Nearest Neighbour (k-NN). …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  9. 9

    Classification of compressive strength grades for lightweight aggregate concrete with palm oil fuel ash (POFA) using kNearest Neighbour (k-NN) by Mohamad Hushnie, Haron, Nur Azzimah, Zamri, Khairunisa, Muthusamy

    Published 2023
    “…Next, the grades of concrete were classified using a machine learning algorithm named k-Nearest Neighbour (k-NN). …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  10. 10

    Distance measure and its application to decision making, medical diagnosis, and pattern recognition problems under complex picture fuzzy sets by Khan Z., Hussain F., Rahim T., Jan R., Boulaaras S.

    Published 2025
    “…Finally, we developed an algorithm using complex picture fuzzy environments and applied it to a practical application concerning decision making, medical diagnosis, and pattern recognition problems. ? …”
    Article
  11. 11

    Enhancement of text representation for Indonesian document summarization with deep sequential pattern mining by Dian Sa’adillah Maylawati

    Published 2023
    “…First, this study combines SPM with Sentence Scoring method as feature-based approach and Bellman-Ford algorithm as graph-based to validate the performance of SPM. …”
    Get full text
    Get full text
    Get full text
    Thesis
  12. 12
  13. 13

    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

    Published 2019
    “…This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
    Get full text
    Get full text
    Thesis
  14. 14

    Spatial-temporal analysis using two-stage clustering and GIS-based MCDM to identify potential market regions by Ernawati, Kamal Baharin, Safiza Suhana, Kasmin, Fauziah

    Published 2021
    “…First, time-series clustering is conducted to groups regencies/cities based on the enrolled students' patterns over time in the university. Subsequently, the origin schools' regencies/cities were clustered using the k- prototypes algorithm based on their time-series pattern category, the consistency in sending students, average cumulative grade point average (CGPA), and dropout (DO) rate. …”
    Get full text
    Get full text
    Get full text
    Article
  15. 15
  16. 16
  17. 17