Search Results - (( java estimation based algorithm ) OR ( program navigation learning algorithm ))

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  1. 1

    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. …”
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    Article
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  3. 3

    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
  4. 4

    Multi-floor indoor location estimation system based on wireless local area network by Chua, Tien Han

    Published 2007
    “…The most probable match is selected and returned as estimated location based on Bayesian filtering algorithm. …”
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    Thesis
  5. 5

    Ant colony optimization algorithm for load balancing in grid computing by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

    Published 2012
    “…Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources.A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against other ant based algorithm, in terms of resource utilization. …”
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    Monograph
  6. 6

    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. …”
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    Monograph
  7. 7

    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. …”
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    Article
  8. 8

    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

    Published 2011
    “…A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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    Thesis
  9. 9

    Resource management in grid computing using ant colony optimization by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

    Published 2011
    “…Resources with high pheromone value are selected to process the submitted jobs.Global pheromone update is performed after completion processing the jobs in order to reduce the pheromone value of resources.A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against other ant based algorithm, in terms of resource utilization.Experimental results show that EACO produced better grid resource management solution.…”
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    Monograph
  10. 10
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    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. …”
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    Thesis
  12. 12

    JTAGGER by YAACOB, NORHANA

    Published 2006
    “…The part-of-speech tagging algorithms fall into three classes which are rule-based taggers, stochastic taggers, and transformation-based taggers. …”
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    Final Year Project
  13. 13

    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. …”
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    Book
  14. 14

    Implementation of RIO in UMJaNetSim / Chan Chin We by Chan, Chin We

    Published 2004
    “…In this project, I will focus on the earliest making algorithm, which is calculating the average queue sizes for in-profile packets and total packets. …”
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    Thesis
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    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.…”
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    Proceeding Paper
  17. 17

    Fuzzy-based multi-agent approach for reliability assessment and improvement of power system protection by Nadheer Abdulridha, Shalash

    Published 2015
    “…The probability agent is to determine the capacity in service while a fuzzy model agent is to estimate the operation or failure probability. In addition, another two agents have been developed based on Monte Carlo simulation. …”
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    Thesis