Search Results - (( feature selection using algorithm ) OR ( java application optimization algorithm ))

Refine Results
  1. 1

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…Features selection process can be considered a problem of global combinatorial optimization in machine learning. …”
    Get full text
    Get full text
    Thesis
  2. 2

    Visdom: Smart guide robot for visually impaired people by Lee, Zhen Ting

    Published 2025
    “…The system architecture integrates ROS 2 on a Raspberry Pi, with TCP/IP connectivity enabling remote operation. An Android mobile application, developed using Java and the java.net.Socket library, provides an intuitive and accessible user interface for seamless interaction with the robot. …”
    Get full text
    Get full text
    Final Year Project / Dissertation / Thesis
  3. 3

    Visdom: Smart guide robot for visually impaired people by Lee, Zhen Ting

    Published 2025
    “…The system architecture integrates ROS 2 on a Raspberry Pi, with TCP/IP connectivity enabling remote operation. An Android mobile application, developed using Java and the java.net.Socket library, provides an intuitive and accessible user interface for seamless interaction with the robot. …”
    Get full text
    Get full text
    Final Year Project / Dissertation / Thesis
  4. 4

    Smart student timetable planner by Wong, Xin Tong

    Published 2025
    “…The system is implemented using Node.js with Express for server-side development, HTML, CSS, and JavaScript for the frontend, and Socket.IO for real-time collaboration. …”
    Get full text
    Get full text
    Final Year Project / Dissertation / Thesis
  5. 5
  6. 6

    Performance evaluation of real-time multiprocessor scheduling algorithms by Alhussian, H., Zakaria, N., Abdulkadir, S.J., Fageeri, S.O.

    Published 2016
    “…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
    Get full text
    Get full text
    Conference or Workshop Item
  7. 7

    Route Optimization System by Zulkifli, Abdul Hayy

    Published 2005
    “…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
    Get full text
    Get full text
    Final Year Project
  8. 8

    Evaluation of feature selection algorithm for android malware detection by Mazlan, Nurul Hidayah, A Hamid, Isredza Rahmi

    Published 2018
    “…The Android features were filtered before detection process using TF-IDF algorithm. …”
    Get full text
    Article
  9. 9

    Feature selection to enhance android malware detection using modified term frequency-inverse document frequency (MTF-IDF) by Mazlan, Nurul Hidayah

    Published 2019
    “…The related best features in the sample are selected using weight and priority ranking process using K-means. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  10. 10
  11. 11

    Enhanced grey wolf optimisation algorithm for feature selection in anomaly detection by Almazini, Hussein

    Published 2022
    “…Experimental results of the EBGWO algorithm on the NSL-KDD dataset in terms of number of selected features and classification accuracy are superior to other benchmark optimisation algorithms. …”
    Get full text
    Get full text
    Thesis
  12. 12

    Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection by Tubishat, Mohammad, Idris, Norisma, Shuib, Liyana, Abushariah, Mohammad A.M., Mirjalili, Seyedali

    Published 2020
    “…An improved version of Salp Swarm Algorithm (ISSA) is proposed in this study to solve feature selection problems and select the optimal subset of features in wrapper-mode. …”
    Get full text
    Get full text
    Article
  13. 13

    Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

    Published 2019
    “…The proposed algorithm is compared with the state-of-the-art feature selection algorithms using three different datasets. …”
    Get full text
    Get full text
    Get full text
    Thesis
  14. 14

    Metaheuristic algorithms for feature selection (2014–2024) by Faizan, Muhammad, Muhammad Arif, Mohamad

    Published 2025
    “…Feature selection is a process used during machine learning and data analysis, aimed at selecting the best features to increase model efficiency, decrease complexity, and increase readability. …”
    Get full text
    Get full text
    Get full text
    Article
  15. 15
  16. 16

    Optimization of attribute selection model using bio-inspired algorithms by Basir, Mohammad Aizat, Yusof, Yuhanis, Hussin, Mohamed Saifullah

    Published 2019
    “…Attribute selection which is also known as feature selection is an essential process that is relevant to predictive analysis.To date, various feature selection algorithms have been introduced, nevertheless they all work independently. …”
    Get full text
    Get full text
    Get full text
    Article
  17. 17
  18. 18

    A New And Fast Rival Genetic Algorithm For Feature Selection by Too, Jing Wei, Abdullah, Abdul Rahim

    Published 2021
    “…The genetic algorithm (GA) as a fundamental optimization tool has been widely used in feature selection tasks. …”
    Get full text
    Get full text
    Get full text
    Article
  19. 19

    Utilizing artificial bee colony algorithm as feature selection method in Arabic text classification by Hijazi, Musab, Zeki, Akram M., Ismail, Amelia Ritahani

    Published 2023
    “…One of the widely used algorithms for feature selection in text classification is the Evolutionary algorithm . …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  20. 20

    Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

    Published 2004
    “…CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
    Get full text
    Get full text
    Thesis