Search Results - (( parameter evaluation bees algorithm ) OR ( parameter evaluation path algorithm ))

Refine Results
  1. 1

    Performance analysis of ZigBeePRO network using shortest path algorithm for Distributed Renewable Generation by Islam, Syed Zahurul, Othman, Mohammad Lutfi, Islam, Syed Zahidul

    Published 2021
    “…Due to this polarization effect, the brick-built type cabin at the DRG site is a consequence of a higher propagation path loss than the Iron (III)-made cabin. The other performance parameters, including network throughput, data loss, and ZigBeePRO collision, are also evaluated.…”
    Get full text
    Get full text
    Article
  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
    “…This study aims to evaluate the effectiveness of two optimization algorithms, artificial bee colony (ABC) and spiral dynamic algorithm (SDA), in controlling the position of a flexible-link manipulator. …”
    Get full text
    Get full text
    Get full text
    Article
  3. 3

    Artificial Bee Colony for Minimizing the Energy Consumption in Mobile Ad Hoc Network by Tareq, M., Abed, S.A., Sundararajan, E.A.

    Published 2019
    “…The evaluation is based on node speed and packet size topology parameters. …”
    Get full text
    Get full text
    Article
  4. 4
  5. 5

    Parameter estimation of essential amino acids in Arabidopsis thaliana using hybrid of bees algorithm and harmony search by Aw, Mei Yee, Mohd Saberi, Mohamad, Chong, Chuii Khim, Safaai, Deris, Muhammad Akmal, Remli, Mohd Arfian, Ismail, Corchado, Juan Manuel, Omatu, Sigeru

    Published 2019
    “…This paper proposes the Hybrid of Bees Algorithm and Harmony Search (BAHS) to estimate the kinetics parameters of essential amino acid production in the aspartate metabolism for Arabidopsis thaliana. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Get full text
    Book Chapter
  6. 6

    Hybrid Artificial Bees Colony Algorithms For Optimizing Carbon Nanotubes Characteristics by Mohammad Jarrah, Mu'ath Ibrahim

    Published 2018
    “…Optimization is a crucial process to select the best parameters in single and multi-objective problems for manufacturing process.However,it is difficult to find an optimization algorithm that obtain the global optimum for every optimization problem.Artificial Bees Colony (ABC) is a well-known swarm intelligence algorithm in solving optimization problems.It has noticeably shown better performance compared to the state-of-art algorithms.This study proposes a novel hybrid ABC algorithm with β-Hill Climbing (βHC) technique (ABC-βHC) in order to enhance the exploitation and exploration process of the ABC in optimizing carbon nanotubes (CNTs) characteristics.CNTs are widely used in electronic and mechanical products due to its fascinating material with extraordinary mechanical,thermal,physical and electrical properties. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  7. 7

    Evaluation of robot path planning algorithms in global static environments: genetic algorithm vs ant colony optimization algorithm / Nohaidda Sariff and Norlida Buniyamin by Sariff, Nohaidda, Buniyamin, Norlida

    Published 2010
    “…Performances between both algorithms were compared and evaluated in terms of speed and number of iterations that each algorithm takes to find an optimal path within several selected environments. …”
    Get full text
    Get full text
    Get full text
    Article
  8. 8

    Multiobjective optimization using weighted sum Artificial Bee Colony algorithm for Load Frequency Control by Naidu, K., Mokhlis, Hazlie, Bakar, Ab Halim Abu

    Published 2014
    “…The robustness of the proposed algorithm is further investigated by evaluating the response of the system under simultaneous step load perturbation (SLP), changing load demand and collectively varying system parameters in the range of ±50%. …”
    Get full text
    Get full text
    Get full text
    Article
  9. 9

    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
  10. 10
  11. 11

    A multi-objective parametric algorithm for sensor-based navigation in uncharted terrains by Khaksar W., Sahari K.S.M.

    Published 2023
    “…These parameters are designed carefully to cover different requirements of the path planner. …”
    Article
  12. 12

    Artificial Bee Colony Algorithm for Pairwise Test Generation by Alazzawi, Ammar K., Homaid, Ameen A. Ba, Alomoush, Alaa A., Alsewari, Abdulrahman A.

    Published 2017
    “…In an attempt to solve this problem, there has been a development of a number of sampling and pairwise strategies in the literature. In this paper, we evaluated and proposed a pairwise strategy named Pairwise Artificial Bee Colony algorithm (PABC). …”
    Get full text
    Get full text
    Get full text
    Article
  13. 13

    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
    “…Subsequently, both algorithms were applied to the test environments. Finally, the performances of both algorithms were analyzed and evaluated based on the required criteria. …”
    Get full text
    Get full text
    Thesis
  14. 14

    An Experiment of Ant Algorithms : Case Study of Kota Kinabalu Central Town by Nor Rafidah, Mohamad

    Published 2005
    “…The objectives of this study are to explore and evaluate the Ant System (AS) algorithm and Ant Colony System (ACS) algorithm in finding shortest paths. …”
    Get full text
    Get full text
    Get full text
    Thesis
  15. 15
  16. 16

    All-pass filtered x least mean square algorithm for narrowband active noise control by Mondal (Das), Kuheli, Das, Saurav, Abu, Aminudin, Hamada, Nozomu, Toh, Hoong Thiam, Das, Saikat, Faris, Waleed Fekry

    Published 2018
    “…The performance evaluation in terms of convergence speed of the proposed algorithm is validated with standard ANC without secondary path modelling. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  17. 17

    Sediment load forecasting from a biomimetic optimization perspective: Firefly and Artificial Bee Colony algorithms empowered neural network modeling in �oruh River by Katipo?lu O.M., Kartal V., Pande C.B.

    Published 2025
    “…This study combined models such as the artificial neural network (ANN) algorithm with the Firefly algorithm (FA) and Artificial Bee Colony (ABC) optimization techniques for the estimation of monthly SL values in the �oruh River in Northeastern Turkey. …”
    Article
  18. 18

    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
  19. 19

    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
  20. 20