Search Results - (( developing navigation learning algorithm ) OR ( java application scheduling algorithm ))

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  1. 1

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

    Published 2016
    “…The CPU profiler of JavaTM VisualVM measures the number of invocations of scheduling event handlers (procedures) in each algorithm as well as the total time spent in all invocations of this handler. …”
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    Conference or Workshop Item
  2. 2

    Advancements and challenges in mobile robot navigation: a comprehensive review of algorithms and potential for self-learning approaches by Al Mahmud, Suaib, Kamarulariffin, Abdurrahman, Mohd Ibrahim, Azhar, Haja Mohideen, Ahmad Jazlan

    Published 2024
    “…In this review paper, a comprehensive review of mobile robot navigation algorithms has been conducted. The findings suggest that, even though the self-learning algorithms require huge amounts of training data and have the possibility of learning erroneous behavior, they possess huge potential to overcome challenges rarely addressed by the other traditional algorithms. …”
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    Article
  3. 3

    A Toolkit for Simulation of Desktop Grid Environment by FOROUSHAN, PAYAM CHINI

    Published 2014
    “…In this type of environment it is nearly impossible to prove the effectiveness of a scheduling algorithm. Hence the main objective of this study is to develop a desktop grid simulator toolkit for measuring and modeling scheduler algorithm performance. …”
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    Final Year Project
  4. 4

    Computer Lab Timetabling Using Genetic Algorithm Case Study - Unit ICT by Abdullah, Amran

    Published 2006
    “…Genetic Algorithm is one of the most popular optimization solutions used in various applications such as scheduling. …”
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    Thesis
  5. 5

    Development of algorithm for improved maze navigation by Ahmad, Faiz Aydil

    Published 2014
    “…This paper describes the development of algorithm for improved maze navigation and it is a continuation on a previous project. …”
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    Final Year Project
  6. 6

    A novel navigation algorithm for collaborative multi robots by Ahmed, Mohiuddin, Khan, Md. Raisuddin, Billah, Md. Masum, Farhana, Soheli

    Published 2010
    “…But present unique challenges for developing collaborative navigation algorithm and coordination among themselves are not sufficient for autonomous collaborative tasks. …”
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    Article
  7. 7

    Improving Class Timetabling using Genetic Algorithm by Qutishat, Ahmed Mohammed Ali

    Published 2006
    “…This paper reports the power fill techniques using GA in scheduling. Class timetabling problem is one of the applications in scheduling. …”
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    Thesis
  8. 8

    Examination timetabling using genetic algorithm case study: KUiTTHO by Mohd Salikon, Mohd Zaki

    Published 2005
    “…This paper reports the powerful techniques using GA in scheduling. Examination timetabling problem is one of the applications in scheduling. …”
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    Thesis
  9. 9

    Examination Timetabling Using Genetic Algorithm Case Study : KUiTTHO by Mohd. Zaki, Mohd. Salikon

    Published 2005
    “…This paper reports the powerful techniques using GA in scheduling. Examination timetabling problem is one of the applications in scheduling. …”
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    Thesis
  10. 10

    A collaborative navigation algorithm for multi-agent robots in autonomous reconnaissance mission by Ahmed, Mohiuddin, Khan, Md. Raisuddin, Billah, Md. Masum, Farhana, Soheli

    Published 2010
    “…But present unique challenges for developing collaborative navigation algorithm and coordination among themselves are not sufficient for autonomous collaborative tasks. …”
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    Proceeding Paper
  11. 11

    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

    Published 2022
    “…Therefore, in this paper, we proposed Dynamic tasks scheduling algorithm based on attribute reduction with an enhanced hybrid Genetic Algorithm and Particle Swarm Optimization for optimal device selection. …”
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    Article
  12. 12

    A Review: Current Trend of Immersive Technologies for Indoor Navigation and the Algorithms by Sariman, Muhammad Shazmin, Othman, Maisara, Mat Akir, Rohaida, Mahamad, Abd Kadir, Ab Rahman, Munirah

    Published 2024
    “…This paper presents a comprehensive review of collective algorithms developed for indoor navigation. The in-depth analysis of these articles concentrates on both advantages and disadvantages, as well as the different types of algorithms used in each article. …”
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    Article
  13. 13
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    Dynamic path planning algorithm in mobile robot navigation by Yun, S.C., Parasuraman, S., Ganapathy, V.

    Published 2011
    “…MATLAB simulation is developed to verify and validate the algorithm before they are real time implemented on Team AmigoBotTM robot. …”
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    Conference or Workshop Item
  15. 15

    Batch mode heuristic approaches for efficient task scheduling in grid computing system by Maipan-Uku, Jamilu Yahaya

    Published 2016
    “…Many algorithms have been implemented to solve the grid scheduling problem. …”
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    Thesis
  16. 16

    IMPLEMENTATION OF BEHAVIOUR BASED NAVIGATION IN A PHYSICALLY CONFINED SITE by ABDUL RAZAK, NUSRAH

    Published 2017
    “…Behaviour-based architecture is one of the most effective autonomous navigation techniques, second only to machine learning. …”
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    Final Year Project
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    Smart student timetable planner by Wong, Xin Tong

    Published 2025
    “…Course data is managed in CSV format, parsed into JSON for fast processing, while sessionStorage and localStorage handle user data within active sessions. A Genetic Algorithm forms the core scheduling engine, generating optimized timetables that respect both hard constraints, such as avoiding clashes, and soft constraints, such as personal preferences.The final output of this project is a functional web-based timetable planner that successfully enhances scheduling efficiency, reduces the likelihood of errors, and improves the overall academic planning experience. …”
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    Final Year Project / Dissertation / Thesis