Search Results - (( java implementation path algorithm ) OR ( programming language classification algorithm ))

Refine Results
  1. 1

    Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer by Ahmad Nezer, Nurul Aqilah

    Published 2017
    “…The development tools used in developing this project is NetBeans by using Java for the implementation of the coding. The methodology that used for developing this system is the Dijkstra’s algorithm. …”
    Get full text
    Get full text
    Thesis
  2. 2

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

    Published 2019
    “…BST inserts the nodes in the way that the Dijkstra’s can find the empty parking in fastest way. Dijkstra’s algorithm initials the paths to finding the shortest path while ACO optimizes the paths. …”
    Get full text
    Get full text
    Thesis
  3. 3

    Path planning for unmanned aerial vehicle (UAV) using rotated accelerated method in static outdoor environment by Shaliza Hayati A. Wahab, Nordin Saad, Azali Saudi, Ali Chekima

    Published 2021
    “…In this study, a fast iterative method known as Rotated Successive Over-Relaxation (RSOR) is introduced. The algorithm is implemented in a self-developed 2D Java tool, UAV Planner. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  4. 4

    Smart appointment organizer for mobile application / Mohd Syafiq Adam by Adam, Mohd Syafiq

    Published 2009
    “…The main component of this prototype is the use of Dijkstra algorithm to compute the shortest path from source of appointment to the 6 points of destinations within UiTM Shah Alam. …”
    Get full text
    Get full text
    Thesis
  5. 5

    An efficient and effective case classification method based on slicing by Shiba, Omar A. A., Sulaiman, Md. Nasir, Mamat, Ali, Ahmad, Fatimah

    Published 2006
    “…This paper introduces a new classification method based on slicing techniques that was proposed for procedural programming languages. …”
    Get full text
    Get full text
    Get full text
    Article
  6. 6

    Dragon Fruit Classification using Convolutional Neural Network by Tan, Ying Zhi

    Published 2020
    “…The project will make use of Deep Learning approach and algorithm with Python programming language for the ripeness classification.…”
    Get full text
    Get full text
    Final Year Project
  7. 7
  8. 8

    Poverty Classification of Central Perak Population Using Machine Learning by P.Rajendran, Kumaran

    Published 2019
    “…In this study, back propagation algorithm and other machine learning algorithm will be used to build models via anaconda using python programming language that can classify each poor household appropriate their poverty status. …”
    Get full text
    Get full text
    Final Year Project
  9. 9
  10. 10

    Improved voting technique for ensemble of MLP system applied on various classification data / Saodah Omar, Iza Sazanita Isa and Junita Mohd Saleh. by Omar, Saodah, Isa, Iza Sazanita, Mohd Saleh, Junita

    Published 2010
    “…The work employs MATLAB Neural Network Toolbox and Borland C++ programming language as the tools to develop the proposed system. …”
    Get full text
    Get full text
    Research Reports
  11. 11

    Analysis Of Personal Protective Equipment Classification Method Using Deep Learning by Siti Zahrah Nur Ain, Silopung

    Published 2022
    “…This classification is performed using Anaconda and Jupyter Notebok Software that use Python as the programming language. …”
    Get full text
    Get full text
    Undergraduates Project Papers
  12. 12
  13. 13
  14. 14

    A De-noising Scheme for Wavelet Based Power Quality Disturbances Detection and Classification system by Keow, Chuah Heng, Nallagownden, Perumal, K. S. , Rama Rao

    Published 2011
    “…The ability of the Classification system can then be restored. To test the effectiveness of the de-noising scheme, the system is tested with noise-added disturbance signals generated by MATLAB programming language and some field data obtained from the PQDIF resource centre. …”
    Get full text
    Article
  15. 15

    A De-noising Scheme for Enhancing Power Quality Problem Classification System Based on Wavelet Transform and Rule-Based Method by Keow, Chuah Heng, Nallagownden, Perumal, K. S. , Rama Rao

    Published 2011
    “…The ability of the Classification system can then be restored. To test the effectiveness of the denoising scheme, the system is tested with noise-added disturbance signals generated by MATLAB programming language and some field data obtained from the PQDIF resource centre. …”
    Get full text
    Conference or Workshop Item
  16. 16

    Object-Oriented Programming semantics representation utilizing agents by Mohd Aris, Teh Noranis

    Published 2011
    “…Generally, these source codes go through the preprocessing, comparison, extraction, generate program semantics and classification processes. A formal algorithm that can be applied to any two related Java-based source codes examples is invented to generate the semantics of these source codes. …”
    Get full text
    Get full text
    Get full text
    Article
  17. 17
  18. 18

    Face classification for three major ethnic of Orang Asli using Back Propagation Neural Network / Nor Intan Shafini Nasaruddin by Nasaruddin, Nor Intan Shafini

    Published 2012
    “…The image classification prototype is developed by using JAVA programming language which is based on supervised learning algorithm, Backpropagation Neural Network. …”
    Get full text
    Get full text
    Thesis
  19. 19

    Towards a better feature subset selection approach by Shiba, Omar A. A.

    Published 2010
    “…The selection of the optimal features subset and the classification has become an important issue in the data mining field.We propose a feature selection scheme based on slicing technique which was originally proposed for programming languages.The proposed approach called Case Slicing Technique (CST).Slicing means that we are interested in automatically obtaining that portion 'features' of the case responsible for specific parts of the solution of the case at hand.We show that our goal should be to eliminate the number of features by removing irrelevant once.Choosing a subset of the features may increase accuracy and reduce complexity of the acquired knowledge.Our experimental results indicate that the performance of CST as a method of feature subset selection is better than the performance of the other approaches which are RELIEF with Base Learning Algorithm (C4.5), RELIEF with K-Nearest Neighbour (K-NN), RELIEF with Induction of Decision Tree Algorithm (ID3) and RELIEF with Naïve Bayes (NB), which are mostly used in the feature selection task.…”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  20. 20