Search Results - (( java simulation optimization algorithm ) OR ( _ navigation learning algorithm ))

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  1. 1
    Advancements and challenges in mobile robot navigation: a comprehensive review of algorithms and potential for self-learning approaches

    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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  2. 2
    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection

    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
    “…The simulation is implemented with iFogSim and java programming language. …”
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  3. 3
    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing

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

    Published 2011
    “…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 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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  4. 4
    Autonomous Visual Navigation using Deep Reinforcement Learning: An Overview

    Autonomous Visual Navigation using Deep Reinforcement Learning: An Overview by Ejaz, M.M., Tang, T.B., Lu, C.-K.

    Published 2019
    “…Reinforcement Learning (RL) algorithm with deep learning techniques helps to solve many complex problems of today's world, such as to play a video game and autonomous navigation in the robots using the raw image as an input. …”
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  5. 5
    Autonomous Visual Navigation using Deep Reinforcement Learning: An Overview

    Autonomous Visual Navigation using Deep Reinforcement Learning: An Overview by Ejaz, M.M., Tang, T.B., Lu, C.-K.

    Published 2019
    “…Reinforcement Learning (RL) algorithm with deep learning techniques helps to solve many complex problems of today's world, such as to play a video game and autonomous navigation in the robots using the raw image as an input. …”
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  6. 6
    Ant colony optimization algorithm for load balancing in grid computing

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

    Published 2012
    “…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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    Monograph
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  7. 7
    Development of algorithm for improved maze navigation

    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
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  8. 8
    A novel navigation algorithm for collaborative multi robots

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

    Published 2010
    “…The goal of multi-agent robots is to move as a cohesive team by sharing their distributed learning behaviors and navigating in autonomous reconnaissance missions. …”
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  9. 9
    A Review: Current Trend of Immersive Technologies for Indoor Navigation and the Algorithms

    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
    “…Based on the findings of this review, we can conclude that an efficient solution for indoor navigation that uses the capabilities of embedded data and technological advances in immersive technologies can be achieved by training the shortest path algorithm with a deep learning algorithm to enhance the indoor navigation system.…”
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  10. 10
    OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT

    OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT by Murad S.S., Badeel R., Alsandi N.S.A., Alshaaya R.F., Ahmed R.A., Muhammed A., Derahman M.

    Published 2023
    “…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. …”
    Review
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  11. 11
    A collaborative navigation algorithm for multi-agent robots in autonomous reconnaissance mission

    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
    “…The goal of multi-agent robots is to move as a cohesive team by sharing their distributed learning behaviors and navigating in autonomous reconnaissance missions. …”
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  12. 12
    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization

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

    Published 2019
    “…This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
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  13. 13
    Dynamic path planning algorithm in mobile robot navigation

    Dynamic path planning algorithm in mobile robot navigation by Yun, S.C., Parasuraman, S., Ganapathy, V.

    Published 2011
    “…In this research, Genetic Algorithm (GA) is used to assist mobile robot to move, identify the obstacles in the environment, learn the environment and reach the desired goal in an unknown and unrecognized environment. …”
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  14. 14
    Features selection for intrusion detection system using hybridize PSO-SVM

    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. …”
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  15. 15
    IMPLEMENTATION OF BEHAVIOUR BASED NAVIGATION IN A PHYSICALLY CONFINED SITE

    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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  16. 16
    A Modified Hybrid Fuzzy Controller for Real-Time Mobile Robot Navigation

    A Modified Hybrid Fuzzy Controller for Real-Time Mobile Robot Navigation by Hossen J., Sayeed S., Iqbal A.K.M.P.

    Published 2023
    “…Algorithms; Controllers; Fuzzy clustering; Fuzzy systems; Intelligent control; Intelligent systems; Learning algorithms; Least squares approximations; Membership functions; Mobile robots; Navigation; Robotics; Robots; Smart sensors; and ANFIS; Apriori algorithms; Fuzzy C mean; Gradient descent algorithms; Hybrid-fuzzy controllers; Mobile Robot Navigation; Subtractive clustering; Subtractive clustering algorithms; Clustering algorithms…”
    Conference Paper
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  17. 17
    Resource management in grid computing using ant colony optimization

    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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  18. 18
    Collision prediction based genetic network programming-reinforcement learning for mobile robot navigation in unknown dynamic environments

    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
    “…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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  19. 19
    Solving robot path planning problem using Ant Colony Optimisation (ACO) approach / Nordin Abu Bakar and Rosnawati Abdul Kudus

    Solving robot path planning problem using Ant Colony Optimisation (ACO) approach / Nordin Abu Bakar and Rosnawati Abdul Kudus by Abu Bakar, Nordin, Abdul Kudus, Rosnawati

    Published 2009
    “…These experimental scenarios represent the respective navigation frameworks found in the literature used to test learning algorithms. …”
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  20. 20
    Advancing mobile robot navigation with DRL and heuristic rewards: a comprehensive review

    Advancing mobile robot navigation with DRL and heuristic rewards: a comprehensive review by Khan, Mazbahur Rahman, Mohd Ibrahim, Azhar, Al Mahmud, Suaib, Samat, Farah Asyiqin, Jasni, Farahiyah, Mardzuki, Muhammad Imran

    Published 2025
    “…The advent of Deep Reinforcement Learning (DRL) has spurred significant research into enabling mobile robots to learn effective navigation by optimizing actions based on environmental rewards. …”
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