Search Results - (( motion succession _ algorithm ) OR ( based optimization based algorithm ))

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  1. 1
    Runtime reduction in optimal multi-query sampling-based motion planning

    Runtime reduction in optimal multi-query sampling-based motion planning by Khaksar W., Sahari K.S.B.M., Ismail F.B., Yousefi M., Ali M.A.

    Published 2023
    “…Algorithms; Dispersions; Manufacture; Query processing; Robotics; High-dimensional; Low dispersions; Optimal solutions; Path length; Planning tasks; Sampling-based; Sampling-based algorithms; Sampling-based motion planning; Motion planning…”
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  2. 2
    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
    “…Sampling-based motion planning is a class of randomized path planning algorithms with proven completeness. …”
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  3. 3
    Design and optimization of Levenberg-Marquardt based Neural Network Classifier for EMG signals to identify hand motions

    Design and optimization of Levenberg-Marquardt based Neural Network Classifier for EMG signals to identify hand motions by Ibrahimy, Muhammad Ibn, Ahsan, Md. Rezwanul, Khalifa, Othman Omran

    Published 2013
    “…The outcomes of the research show that the optimal design of Levenberg-Marquardt based neural network classifier can perform well with an average classification success rate of 88.4%. …”
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  4. 4
    Rule-Based Multi-State Gravitational Search Algorithm for Discrete Optimization Problem

    Rule-Based Multi-State Gravitational Search Algorithm for Discrete Optimization Problem by Ismail, Ibrahim, Zuwairie, Ibrahim, Zulkifli, Md. Yusof

    Published 2015
    “…Gravitational search algorithm swarm (GSA) is a metaheuristic optimization algorithm, which is based on the Newton's law of gravity and the law of motion, has been successfully applied to solve various optimization problems in real-value search space. …”
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  5. 5
    A review on particle swarm optimization algorithm and its variants to human motion tracking

    A review on particle swarm optimization algorithm and its variants to human motion tracking by Saini, S., Rambli, D.R.B.A., Zakaria, M.N.B., Sulaiman, S.B.

    Published 2014
    “…Several approaches have been proposed in the literature using different techniques.However, conventional approaches such as stochastic particle filtering have shortcomings in computational cost, slowness of convergence, suffers from the curse of dimensionality and demand a high number of evaluations to achieve accurate results. Particle swarm optimization (PSO) is a population-based globalized search algorithm which has been successfully applied to address human motion tracking problem and produced better results in high-dimensional search space.This paper presents a systematic literature survey on the PSO algorithm and its variants to human motion tracking. …”
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  6. 6
    A Navigation Strategy for Swarm Robotics Based on Bat Algorithm Optimization Technique

    A Navigation Strategy for Swarm Robotics Based on Bat Algorithm Optimization Technique by Nur Aisyah Syafinaz, Suarin, Pebrianti, Dwi, Bayuaji, Luhur, Muhammad, Syafrullah, Zulkifli, Musa

    Published 2018
    “…This paper aims to adapt Bat Algorithm (BA) optimization techniques to the swarm robotics system. …”
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  7. 7
    Multi-state PSO GSA for solving discrete combinatorial optimization problems

    Multi-state PSO GSA for solving discrete combinatorial optimization problems by Ismail, Ibrahim

    Published 2016
    “…Two examples of meta-heuristics are Particle swarm optimization (PSO) and gravitational search algorithm (GSA), which are based on the social behavior of bird flocks and the Newton's law of gravity and the law of motion, respectively. …”
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  8. 8
    A new variant of black hole algorithm based on multi population and levy flight for clustering problem

    A new variant of black hole algorithm based on multi population and levy flight for clustering problem by Haneen Abdul Wahab, Abdul Raheem

    Published 2020
    “…Meta-heuristic algorithm has been successfully implemented on data clustering problems seeking a near optimal solution in terms of quality of the resultant clusters. …”
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  9. 9
    Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms

    Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms by Koh, Johnny Siaw Paw

    Published 2008
    “…The representation approach has been implemented via a computer program in order to achieve optimized scanning performance. This algorithm has been tested and implemented successfully via a dual beam optical scanning system.…”
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  10. 10
    EMG motion pattern classification through design and optimization of neural network

    EMG motion pattern classification through design and optimization of neural network by Ahsan, Md. Rezwanul, Ibrahimy, Muhammad Ibn, Khalifa, Othman Omran

    Published 2012
    “…The results show that the designed network is optimized for 10 hidden neurons with 7 input features and able to efficiently classify single channel EMG signals with an average success rate of 88.4%. …”
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  11. 11
    An enhanced motion planning method for industrial robots based on the digital twin concept

    An enhanced motion planning method for industrial robots based on the digital twin concept by Rui, Fan

    Published 2025
    “…This study proposes a novel motion planning method for six-degree-of-freedom industrial robots based on DT technology. …”
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  12. 12
    Design, development and performance optimization of a new artificial intelligent controlled multiple-beam optical scanning module

    Design, development and performance optimization of a new artificial intelligent controlled multiple-beam optical scanning module by Koh J.S.P., Aris I.B., Ramachandaramurthy V.K., Bashi S.M., Marhaban M.H.

    Published 2023
    “…This algorithm has been tested and implemented successfully via a dual-beam optical scanning module. � 2006 Asian Network for Scientific Information.…”
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  13. 13
    Design, development and performance optimization of a new artificial intelligent controlled multiple-beam optical scanning module

    Design, development and performance optimization of a new artificial intelligent controlled multiple-beam optical scanning module by Koh J.S.P., Aris I.B., Ramachandaramurthy V.K., Bashi S.M., Marhaban M.H.

    Published 2023
    “…This algorithm has been tested and implemented successfully via a dual-beam optical scanning module. � 2006 Asian Network for Scientific Information.…”
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  14. 14
    EMG motion pattern classification through design and optimization of Neural Network

    EMG motion pattern classification through design and optimization of Neural Network by Md. Rezwanul, Ahsan, Muhammad Ibn, Ibrahimy, Othman Omran, Khalifa

    Published 2012
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  15. 15
    Marine Predator Algorithm and Related Variants: A Systematic Review

    Marine Predator Algorithm and Related Variants: A Systematic Review by Philibus, Emmanuel, Mohd Zain, Azlan, Prasetya, Didik Dwi, Bahari, Mahadi, Yusup, Norfadzlan, Abdul Jalil, Rozita, Abdul Majid, Mazlina, A Samah, Azurah

    Published 2025
    “…It is a population-based metaheuristic optimization algorithm inspired by the general foraging behavior exhibited in the form of Levy and Brownian motion in ocean predators supported by the policy of optimum success rate found in the biological relationship between prey and predators. …”
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  16. 16
    Marine Predator Algorithm and Related Variants: A Systematic Review

    Marine Predator Algorithm and Related Variants: A Systematic Review by Philibus, Emmanuel, Mohd Zain, Azlan, Dwi Prasetya, Didik, Bahari, Mahadi, Yusup, Norfadzlan, Abdul Jalil, Rozita, Abdul Majid, Mazlina, A Samah, Azurah

    Published 2025
    “…It is a population-based metaheuristic optimization algorithm inspired by the general foraging behavior exhibited in the form of Levy and Brownian motion in ocean predators supported by the policy of optimum success rate found in the biological relationship between prey and predators. …”
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  17. 17
    Motion planning and control for autonomous vehicle collision avoidance systems using potential field-based parameter scheduling

    Motion planning and control for autonomous vehicle collision avoidance systems using potential field-based parameter scheduling by Nurbaiti, Wahid, Hairi, Zamzuri, Noor Hafizah, Amer, Dwijotomo, Abdurahman, Sarah ‘Atifah, Saruchi

    Published 2024
    “…A particle swarm optimization algorithm is used to optimize the knowledge database information that is developed based on the perception of driver toward risk in the driving environment. …”
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  18. 18
    Motion planning and control for autonomous vehicle collision avoidance systems using potential field-based parameter scheduling

    Motion planning and control for autonomous vehicle collision avoidance systems using potential field-based parameter scheduling by Nurbaiti, Wahid, Hairi, Zamzuri, Noor Hafizah, Amer, Dwijotomo, Abdurahman, Sarah ‘Atifah, Saruchi

    Published 2024
    “…A particle swarm optimization algorithm is used to optimize the knowledge database information that is developed based on the perception of driver toward risk in the driving environment. …”
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  19. 19
    A study on model-free approach for liquid slosh suppression based on stochastic approximation

    A study on model-free approach for liquid slosh suppression based on stochastic approximation by Ahmad, Mohd Ashraf

    “…In addition, the performance of the SPSA based methods is compared to the other stochastic optimization based approaches, which also includes the variants of SPSA based method, such as Global SPSA. …”
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    Research Report
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  20. 20
    Marine Predator Algorithm and Related Variants: A Systematic Review

    Marine Predator Algorithm and Related Variants: A Systematic Review by Emmanuel, Philibus, Azlan, Mohd Zain, Didik Dwi, Prasetya, Mahadi, Bahari, Norfadzlan, Yusup, Rozita, Abdul Jalil, Mazlina, Abdul Majid, Azurah, A Samah

    Published 2025
    “…It is a population-based metaheuristic optimization algorithm inspired by the general foraging behavior exhibited in the form of Levy and Brownian motion in ocean predators supported by the policy of optimum success rate found in the biological relationship between prey and predators. …”
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