Search Results - (( initial solving path algorithm ) OR ( parameter optimization sensor algorithm ))*

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  1. 1
    A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments

    A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments by Khaksar, Weria

    Published 2013
    “…Afterward, a genetic algorithm-based optimization framework was designed to improve the interpretability and accuracy of the proposed fuzzy-tabu controller by optimizing the parameters of the FLC and also some of the planner’s parameters in order to improve the quality of the generated paths and runtimes of the planner and also to decrease the variation of the results in different runs of the planner. …”
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  2. 2
    Modeling and control of a Pico-satellite attitude using Fuzzy Logic Controller

    Modeling and control of a Pico-satellite attitude using Fuzzy Logic Controller by Zaridah, Mat Zain

    Published 2010
    “…Genetic Algorithm (GA) is a computational model inspired by evaluation. …”
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  3. 3
    Search algorithms for path planning problems in harsh wireless sensor network environment

    Search algorithms for path planning problems in harsh wireless sensor network environment by Hong, Siaw Swin

    Published 2017
    “…Each algorithm solves its respective problem with Enhanced D* solving long initial delay in dynamic environment, NBN solves harsh conditions with limited computational power, and FWN optimized the result of TSP path planning problem with minimal computational effort. …”
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  4. 4
    An Integrated RRT*SMART-A* Algorithm for solving the Global Path Planning Problem in a Static Environment

    An Integrated RRT*SMART-A* Algorithm for solving the Global Path Planning Problem in a Static Environment by Suwoyo, Heru, Adriansyah, Andi, Andika, Julpri, Ubaidillah, Abu

    Published 2023
    “…Thus, RRT*-Smart, a further development of RRT*, is considered ideal for solving RRT* problems. Unlike RRT*, RRT*-Smart applies a path optimization by removing the redundant nodes from the initial path when it is gained. …”
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  5. 5
    AN INTEGRATED RRT*SMART-A* ALGORITHM FOR SOLVING THE GLOBAL PATH PLANNING PROBLEM IN A STATIC ENVIRONMENT

    AN INTEGRATED RRT*SMART-A* ALGORITHM FOR SOLVING THE GLOBAL PATH PLANNING PROBLEM IN A STATIC ENVIRONMENT by SUWOYO, HERU, ADRIANSYAH, ANDI, ANDIKA, JULFRI, SHAMSUDIN, ABU UBAIDAH, ZAKARIA, MOHAMAD FAUZI

    Published 2023
    “…Thus, RRT*-Smart, a further development of RRT*, is considered ideal for solving RRT* problems. Unlike RRT*, RRT*-Smart applies a path optimization by removing the redundant nodes from the initial path when it is gained. …”
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  6. 6
    AN INTEGRATED RRT*SMART-A* ALGORITHM FOR SOLVING THE GLOBAL PATH PLANNING PROBLEM IN A STATIC ENVIRONMENT

    AN INTEGRATED RRT*SMART-A* ALGORITHM FOR SOLVING THE GLOBAL PATH PLANNING PROBLEM IN A STATIC ENVIRONMENT by Suwayo, Heri, Adrishah, Andi, Andika, Juleri, Shamdudin, Abu Ubaidah, Zakaria, Mohamad Fauzi

    Published 2023
    “…Thus, RRT*-Smart, a further development of RRT*, is considered ideal for solving RRT* problems. Unlike RRT*, RRT*-Smart applies a path optimization by removing the redundant nodes from the initial path when it is gained. …”
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  7. 7
    AN INTEGRATED RRT*SMART-A* ALGORITHM FOR SOLVING THE GLOBAL PATH PLANNING PROBLEM IN A STATIC ENVIRONMENT

    AN INTEGRATED RRT*SMART-A* ALGORITHM FOR SOLVING THE GLOBAL PATH PLANNING PROBLEM IN A STATIC ENVIRONMENT by SUWOYO, HERU, ADRIANSHAH, ANDI, ANDIKA, JULPRI, SHAMSUDIN, ABU UBAIDAH, ZAKARIA, MOHAMAD FAUZI

    Published 2023
    “…Thus, RRT*-Smart, a further development of RRT*, is considered ideal for solving RRT* problems. Unlike RRT*, RRT*-Smart applies a path optimization by removing the redundant nodes from the initial path when it is gained. …”
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  8. 8
    AN INTEGRATED RRT*SMART-A* ALGORITHM FOR SOLVING THE GLOBAL PATH PLANNING PROBLEM IN A STATIC ENVIRONMENT

    AN INTEGRATED RRT*SMART-A* ALGORITHM FOR SOLVING THE GLOBAL PATH PLANNING PROBLEM IN A STATIC ENVIRONMENT by HERU SUWOYO, HERU SUWOYO, ANDI ADRIANSYAH, ANDI ADRIANSYAH, JULPRI ANDIKA, JULPRI ANDIKA, SHAMSUDIN, A LT UBAIDAH, ZAKARIA, MOHAMAD FAUZI

    Published 2023
    “…Thus, RRT*-Smart, a further development of RRT*, is considered ideal for solving RRT* problems. Unlike RRT*, RRT*-Smart applies a path optimization by removing the redundant nodes from the initial path when it is gained. …”
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  9. 9
    AN INTEGRATED RRT*SMART-A* ALGORITHM FOR SOLVING THE GLOBAL PATH PLANNING PROBLEM IN A STATIC ENVIRONMENT

    AN INTEGRATED RRT*SMART-A* ALGORITHM FOR SOLVING THE GLOBAL PATH PLANNING PROBLEM IN A STATIC ENVIRONMENT by Heru Sowoyo, Heru Sowoyo, Andi Adrianshah, Andi Adrianshah, Julpri Andika, Julpri Andika, Shamsuddin, Abu Ubaidah, Zakaria, Mohamad Fauzi

    Published 2023
    “…Thus, RRT*-Smart, a further development of RRT*, is considered ideal for solving RRT* problems. Unlike RRT*, RRT*-Smart applies a path optimization by removing the redundant nodes from the initial path when it is gained. …”
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  10. 10
    AN INTEGRATED RRT*SMART-A* ALGORITHM FOR SOLVING THE GLOBAL PATH PLANNING PROBLEM IN A STATIC ENVIRONMENT

    AN INTEGRATED RRT*SMART-A* ALGORITHM FOR SOLVING THE GLOBAL PATH PLANNING PROBLEM IN A STATIC ENVIRONMENT by SUWOYO, HERU, ADRIANSYAH, ANDI, JULI RI ANDIKA, JULI RI ANDIKA, SHAMSUDIN, ABU UBAIDAH, ZAKARIA, MOHAMAD FAUZI

    Published 2023
    “…Thus, RRT*-Smart, a further development of RRT*, is considered ideal for solving RRT* problems. Unlike RRT*, RRT*-Smart applies a path optimization by removing the redundant nodes from the initial path when it is gained. …”
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  11. 11
    Path planning algorithm for a car like robot based on MILP method

    Path planning algorithm for a car like robot based on MILP method by Mohd Sadri, Mohd Pawzi

    Published 2013
    “…This algorithm provides the robot the possibility to move from the initial position to the final position (target). …”
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  12. 12
    Development of an improved Jellyfish Search (JS) algorithm for solving the optimal path problem of multi-robot collaborative multi-tasking in complex vertical farms

    Development of an improved Jellyfish Search (JS) algorithm for solving the optimal path problem of multi-robot collaborative multi-tasking in complex vertical farms by Shen, Jiazheng, Tang, Saihong, Zhao, Ruixin, Fan, Luxin, Mohd Ariffin, Mohd Khairol Anuar, As’arry, Azizan

    Published 2025
    “…The VFSMRCTP model is solved using the TLDW-JS algorithm and a number of comparison algorithms in order to analyze the algorithm’s performance. …”
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  13. 13
    Guidance system based on Dijkstra-ant colony algorithm with binary search tree for indoor parking system

    Guidance system based on Dijkstra-ant colony algorithm with binary search tree for indoor parking system by Mohammad Ata, Karimeh Ibrahim, Che Soh, Azura, Ishak, Asnor Juraiza, Jaafar, Haslina

    Published 2021
    “…A common algorithm to solve the single-source shortest path (SSSP) is the Dijkstra algorithm. …”
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  14. 14
    AN INTEGRATED RRT*SMART-A* ALGORITHM FOR SOLVING THE GLOBAL PATH PLANNING PROBLEM IN A STATIC ENVIRONMENT

    AN INTEGRATED RRT*SMART-A* ALGORITHM FOR SOLVING THE GLOBAL PATH PLANNING PROBLEM IN A STATIC ENVIRONMENT by SUW, HERU, MI ATILTIANSYAH, AN, ANDIKA, JULI RI, SHAVISUDIN, UBAIDAH, AUZI ZAICARIX, M °H MAD

    Published 2023
    “…Thus, RRT*-Smart, a further development of RRT*, is considered ideal for solving RRT* problems. Unlike RRT*, RRT*-Smart applies a path optimization by removing the redundant nodes from the initial path when it is gained. …”
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  15. 15
    AN INTEGRATED RRT*SMART-A* ALGORITHM FOR SOLVING THE GLOBAL PATH PLANNING PROBLEM IN A STATIC ENVIRONMENT

    AN INTEGRATED RRT*SMART-A* ALGORITHM FOR SOLVING THE GLOBAL PATH PLANNING PROBLEM IN A STATIC ENVIRONMENT by SUW, HERU, AtiltIANSYAH, AN- MI, RI ANDIKA, JULI, SHAVISUDIN, UBAIDAH, AUZI ZAICARIX, M °H MAD

    Published 2023
    “…Thus, RRT*-Smart, a further development of RRT*, is considered ideal for solving RRT* problems. Unlike RRT*, RRT*-Smart applies a path optimization by removing the redundant nodes from the initial path when it is gained. …”
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  16. 16
    Solving the optimal path planning of a mobile robot using improved Q-learning

    Solving the optimal path planning of a mobile robot using improved Q-learning by Low, Ee Soong, Ong, Pauline, Cheah, Kah Chun

    Published 2019
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  17. 17
    Multi-mobile agent itinerary planning algorithms for data gathering in wireless sensor networks: a review paper

    Multi-mobile agent itinerary planning algorithms for data gathering in wireless sensor networks: a review paper by Qadori, Huthiafa Q., Ahmad Zukarnain, Zuriati, Mohd Hanapi, Zurina, Subramaniam, Shamala

    Published 2017
    “…The review shows that most of the algorithms used one parameter to find the optimal number of mobile agents in multi-agent itinerary planning without utilizing other parameters. …”
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  18. 18
    Performance comparison between genetic algorithm and ant colony optimization algorithm for mobile robot path planning in global static environment / Nohaidda Sariff

    Performance comparison between genetic algorithm and ant colony optimization algorithm for mobile robot path planning in global static environment / Nohaidda Sariff by Sariff, Nohaidda

    Published 2011
    “…The objective is to verify and compare the effectiveness of both algorithms in finding the optimal robot path in different types of global map environments. …”
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  19. 19
    Parameter adaptation for ant colony system in wireless sensor network

    Parameter adaptation for ant colony system in wireless sensor network by Abdul Nasir, Husna Jamal, Ku-Mahamud, Ku Ruhana, Kamioka, Eiji

    Published 2019
    “…The Ant Colony System (ACS) algorithm has been applied in solving packet routing problems in Wireless Sensor Networks (WSNs). …”
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  20. 20
    Simulated Kalman Filter algorithms for solving optimization problems

    Simulated Kalman Filter algorithms for solving optimization problems by Nor Hidayati, Abdul Aziz

    Published 2019
    “…In the benchmarking of the SKF and ssSKF algorithms’ performance in solving the 14-hole PCB drill path optimization case study with recent implementations, on average, both algorithms show the ability to converge to the optimal solution at a smaller number of function evaluations compared to the Gravitational Search Algorithm (GSA), Cuckoo Search (CS), and Intelligent Water Drop (IWD), although fall-short to the Taguchi- Genetic Algorithm optimization algorithm.…”
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