Search Results - (( parameter optimization method algorithm ) OR ( parameter adaptation path algorithm ))

Refine Results
  1. 1

    Adaptive route optimization for mobile robot navigation using evolutionary algorithm by Kit Guan Lim, Guan Lim, Yoong Hean Lee, Hean Lee, Min Keng Tan, Keng Tan, Hou, Pin Yoong, Tienlei, Wang, Tze, Kenneth Kin Teo

    Published 2021
    “…For example, Ant Colony Optimization (ACO) is an optimization algorithm based on swarm intelligence which is widely used to solve path planning problem. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Proceedings
  2. 2

    Comparative analysis of spiral dynamic algorithm and artificial bee colony optimization for position control of flexible link manipulators by Nor Maniha, Abdul Ghani, Nizaruddin, M. Nasir, Azrul Azim, Abdullah Hashim

    Published 2024
    “…By integrating the ABC algorithm into the manipulator's control system, the goal is to enhance its ability to plan paths and optimize trajectories. …”
    Get full text
    Get full text
    Get full text
    Article
  3. 3

    Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms by Ridha, Hussein Mohammed

    Published 2020
    “…A new mutation vector inspired by the two-opposite path (2-Opt) algorithm with adaptive mutation scalar (F ) and crossover rate (CR) control parameters were employed to enhance the exploration and exploitation phases of the proposed algorithm. …”
    Get full text
    Get full text
    Thesis
  4. 4

    Minimization of tool path length of drilling process using particle swarm optimization (PSO) by Abdullah, Haslina, Zaman, Nizam Nurehsan, Talib, Norfazillah, Lee, Woon Kiow, Saleh, Aslinda, Zakaria, Mohamad Shukri

    Published 2020
    “…In various publications and articles, scientists and researchers adapted several methods of artificial intelligence (AI) or hybrid optimization method for tool path artificial immune system (AIS), genetic algorithms (GA), Artificial Neural networks (ANN) Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO) (Narooei and Ramli, 2014). …”
    Get full text
    Get full text
    Book Section
  5. 5

    A new routing mechanism for energy-efficient in bluetooth mesh-low power nodes based on wireless sensor network by Almuslehi, Hussein Saad Mohammed

    Published 2023
    “…Compared to the Ant Colony Optimization-Genetic Algorithm (ACO-GA) and Ant Colony Optimization- Hierarchical Clustering Mechanism (ACOHCM), the ACO algorithm shows superior power savings and efficiency. …”
    Get full text
    Get full text
    Get full text
    Thesis
  6. 6

    Adaptive model predictive control based on wavelet network and online sequential extreme learning machine for nonlinear systems by Salih, Dhiadeen Mohammed

    Published 2015
    “…The WNMPC is developed by a proposed algorithm named adaptive updating rule (AUR) used with gradient descent optimization method to minimize a constrained cost function over the prediction and control horizons and to offer a robust control performances. …”
    Get full text
    Get full text
    Thesis
  7. 7

    Resource Efficient For Hybrid Fiber-Wireless Communications Links In Access Networks With Multi Response Optimization Algorithm by Wong, Adam Yoon Khang, Indra, Win Adiyansyah, Jamil Alsayaydeh, Jamil Abedalrahim, Mohamat Gani, Johar Akbar, M. Idrus, Sevia, Pusppanathan, Jaysuman

    Published 2021
    “…This work proposes a Multi response Optimization (MO) algorithm, named MO-LMMHOWAN that apply in Last Mile Mobile Hybrid Optical Wireless Access Network (LMMHOWAN). …”
    Get full text
    Get full text
    Get full text
    Article
  8. 8

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

    Published 2010
    “…The predictor is a one step-ahead predictor which estimates the required control at the next sampling time and applies to the system at current sampling time. Finally the adaptive portion of FLC is applied in order to compensate the effect of unknown parameter variations in the Pico-satellite system by using an adaptable gain which is connected in the forward path of the FLC. …”
    Get full text
    Thesis
  9. 9

    Performance comparisons between PID and adaptive PID controllers for travel angle control of a bench-top helicopter by Mansor, Hasmah, Mohd Noor, Samsul Bahari, Gunawan, Teddy Surya, Khan, Sheroz, Othman, N. I., Tazali, N., Islam, R. B.

    Published 2015
    “…Two adaptive algorithms those are pole-placement and deadbeat have been chosen as the method to achieve optimal controller’s parameters. …”
    Get full text
    Get full text
    Get full text
    Article
  10. 10

    Attack path selection optimization with adaptive genetic algorithms by Abd Rahman, A.S., Zakaria, M.N., Masrom, S.

    Published 2016
    “…It calculates the appropriate adjustments for the control parameters such as selection and crossover rate. Possible attack paths are then identified and evaluated based on an attack graph representing the network under study. …”
    Get full text
    Get full text
    Article
  11. 11

    Attack path selection optimization with adaptive genetic algorithms by Abd Rahman, A.S., Zakaria, M.N., Masrom, S.

    Published 2016
    “…It calculates the appropriate adjustments for the control parameters such as selection and crossover rate. Possible attack paths are then identified and evaluated based on an attack graph representing the network under study. …”
    Get full text
    Get full text
    Article
  12. 12

    Adaptive rapidly-exploring-random-tree-star (Rrt*) -Smart: algorithm characteristics and behavior analysis in complex environments by Jauwairia Nasir, Fahad Islam, Yasar Ayaz

    Published 2013
    “…This paper presents a new scheme for RRT*-Smart that helps it to adapt to various types of environments by tuning its parameters during planning based on the information gathered online. …”
    Get full text
    Get full text
    Get full text
    Article
  13. 13

    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
  14. 14
  15. 15

    Optimization of turning parameters using genetic algorithm method by Shah Izwandi, Mohd Zawawi

    Published 2008
    “…This study about development of optimization for turning parameters based on the Genetic Algorithm (GA). …”
    Get full text
    Get full text
    Undergraduates Project Papers
  16. 16

    Parameters optimization of surface grinding process with particles swarm optimization, gravitational search, and sine cosine algorithms: a comparative analysis by Asrul, Adam

    Published 2018
    “…The efficiency of the three algorithms are evaluated and compared with previous results obtained by other optimization methods on similar studies. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  17. 17

    Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization by Nur Iffah, Mohamed Azmi

    Published 2014
    “…Particle swarm optimization algorithm (PSO) is one of the artificial intelligence methods. …”
    Get full text
    Get full text
    Thesis
  18. 18

    Optimization of turning parameters using ant colony optimization by Mohamad Nazri, Semoin

    Published 2008
    “…The project objectives are to develop Ant Colony Optimization (ACO) algorithm for CNC turning process and to optimize turning parameters for minimized production cost per unit. …”
    Get full text
    Get full text
    Undergraduates Project Papers
  19. 19

    Parameter estimation in double exponential smoothing using genetic algorithm / Foo Fong Yeng, Lau Gee Choon and Zuhaimy Ismail by Foo, Fong Yeng, Lau, Gee Choon, Ismail, Zuhaimy

    Published 2014
    “…Trial and error often serves as the best method to determine the parameter. Therefore, a good optimization technique is required for identify the best parameter in minimizing the forecast errors. …”
    Get full text
    Get full text
    Research Reports
  20. 20