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

Refine Results
  1. 1
  2. 2
  3. 3
  4. 4
  5. 5
  6. 6
  7. 7
  8. 8
  9. 9
  10. 10

    The impact of executive function and aerobic exercise recognition in obese children under deep learning by JING, XIN, ABDULLAH, BORHANNUDIN, ABU SAAD, HAZIZI, YANG, XIANGKUN

    Published 2025
    “…Initially, a motion recognition model based on STN and Lucas–Kanade optical flow algorithm optimization was constructed. …”
    Get full text
    Get full text
    Article
  11. 11

    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. …”
    Get full text
    Get full text
    Thesis
  12. 12

    Performance evaluation of Black Hole Algorithm, Gravitational Search Algorithm and Particle Swarm Optimization by Zuwairie, Ibrahim, Mohamad Nizam, Aliman, Fardila, Naim, Sophan Wahyudi, Nawawi, Shahdan, Sudin

    Published 2015
    “…Particle Swarm Optimization (PSO) and Gravitational Search Algorithm are a well known population-based heuristic optimization techniques. …”
    Get full text
    Get full text
    Get full text
    Article
  13. 13

    DESIGN OPTIMIZATION OF A BLDC MOTOR BY GENETIC ALGORITHM AND SIMULATED ANNEALING by K. S. , Rama Rao, Azrul, Hisham Bin Othman

    Published 2007
    “…Single and multi-objective functions of the motor are derived based on the steady state mathematical model. A constrained optimization on the objective function is performed using Genetic Algorithm (GA) and Simulated Annealing (SA), and optimal parameters are obtained. …”
    Get full text
    Get full text
    Conference or Workshop Item
  14. 14

    Design optimization of a bldc motor by genetic algorithm and simulated annealing by K.S.R., Rao, A.H.B., Othman

    Published 2007
    “…Single and multi-objective functions of the motor are derived based on the steady state mathematical model. A constrained optimization on the objective function is performed using Genetic Algorithm (GA) and Simulated Annealing (SA), and optimal parameters are obtained. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  15. 15

    Accelerated black hole optimization algorithm with enhanced FOPID controller for omni-wheel drive mobile robot system by Basil, Noorulden, Marhoon, Hamzah M., Sahib, Dheyaaldeen Faez, Mohammed, Abdullah Fadhil, Ridha, Hussein Mohammed, Ma’arif, Alfian

    Published 2025
    “…To optimize controller performance, six different optimization algorithms are compared are Accelerated Convergence Black Hole Optimization (ACBHO), Black Hole Optimization (BHO), Aquila Optimizer (AO), Hybrid Firefly Particle Swarm Optimization (HFPSO), Enhanced JAYA (EJAYA), and Sunflower Optimizer (SFO). …”
    Get full text
    Get full text
    Get full text
    Article
  16. 16

    PID-based control of a single-link flexible manipulator in vertical motion with genetic optimisation by Md Zain, Badrul Aisham, Tokhi, M. Osman, Toha, Siti Fauziah

    Published 2009
    “…This paper presents an investigation into dynamic simulation and controller optimization based on genetic algorithms (GAs) for a single-link flexible manipulator system in vertical plane motion. …”
    Get full text
    Get full text
    Get full text
    Proceeding Paper
  17. 17

    Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence by S. S. S. , Ranjit

    Published 2011
    “…There are several block-matching algorithm based on block-based motion estimation techniques have been developed. …”
    Get full text
    Get full text
    Get full text
    Book Chapter
  18. 18
  19. 19
  20. 20

    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
    “…Number of iterations and accuracy of localization are presented and compared with navigation strategy based on Particle Swarm Optimization (PSO). The analysis of the performance of proposed algorithm is conducted by considering two different parameters. …”
    Get full text
    Get full text
    Conference or Workshop Item