Search Results - (( java optimization svm algorithm ) OR ( program navigation learning algorithm ))

  • Showing 1 - 11 results of 11
Refine Results
  1. 1

    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. …”
    Get full text
    Get full text
    Thesis
  2. 2

    Collision prediction based genetic network programming-reinforcement learning for mobile robot navigation in unknown dynamic environments by Findi, Ahmed H. M., Marhaban, Mohammad Hamiruce, Raja Ahmad, Raja Mohd Kamil, Hassan, Mohd Khair

    Published 2017
    “…The problem of determining a smooth and collision-free path with maximum possible speed for a Mobile Robot (MR) which is chasing a moving target in a dynamic environment is addressed in this paper. Genetic Network Programming with Reinforcement Learning (GNP-RL) has several important features over other evolutionary algorithms such as it combines offline and online learning on the one hand, and it combines diversified and intensified search on the other hand, but it was used in solving the problem of MR navigation in static environment only. …”
    Get full text
    Get full text
    Article
  3. 3
  4. 4

    An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

    Published 2015
    “…Feature subset selection and classifier ensemble learning are familiar techniques with high ability to optimize above problems. Recently, various techniques based on different algorithms have been developed. …”
    Get full text
    Get full text
    Thesis
  5. 5

    Deep Reinforcement Learning For Control by Bakar, Nurul Asyikin Abu

    Published 2021
    “…As a consequence, the agent is expected to have trained behaviors and navigation without crashing. The complete project is carried out in the CARLA simulator to determine how to operate in discrete action space using Deep Reinforcement Learning (DRL) algorithms. …”
    Get full text
    Get full text
    Monograph
  6. 6

    Optimized processing of satellite signal via evolutionary search algorithm by Hassan, Azmi, Othman, Rusli, Tang, Kieh Ming

    Published 2000
    “…Researchers from the Satellite Navigation Research Group (SNAG) of UTM are currently conducting a research program that mitigates the effect of the Anti-Spoofing (AS) policy. …”
    Get full text
    Get full text
    Article
  7. 7
  8. 8

    Designing machine learning frameworks for intelligence and gamification research / Nordin Abu Bakar by Abu Bakar, Nordin

    Published 2016
    “…Machine learning frameworks have been utilised to facilitate intelligence as operational mechanism in intelligence embedded system such as learning system, prediction protocol and robot navigation system. …”
    Get full text
    Get full text
    Thesis
  9. 9

    Robotics in Education by Norashikin, M. Thamrin, Addie, Irawan, Zurita, Zulkifli, Syed Abdul Mutalib, Al Junid, Megat Syahirul Amin, Megat Ali, Anwar P. P., Abdul Majeed

    Published 2026
    “…The AI section discusses machine learning, path-planning algorithms (e.g., A* search, SLAM), and classroom case studies. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Book
  10. 10
  11. 11

    Double Deep RL-based strategy for UAV-assisted energy harvesting optimization in disaster-resilient IoT networks by Elmadina, Nahla Nur, Saeed, Rashid A, Saeid, Elsadig, Ali, Elmustafa Sayed, Nafea, Ibtehal, Ahmed, Mayada A, Mokhtar, Rania A, Khalifa, Othman Omran

    Published 2024
    “…Due to the problem's complexity, we propose a lightweight DDRL solution capable of efficiently learning system dynamics. Extensive simulations and comparisons with Deep RL and DDPG algorithms demonstrate the superior performance of DDRL in enhancing EH, covering strategic locations effectively, and achieving high satisfaction and accuracy rates.…”
    Get full text
    Get full text
    Get full text
    Get full text
    Proceeding Paper