Search Results - (( parameter optimization method algorithm ) OR ( weight distribution methods algorithm ))

Refine Results
  1. 1

    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
  2. 2
  3. 3

    A firefly algorithm based hybrid method for structural topology optimization by Gebremedhen, H.S., Woldemichael, D.E., Hashim, F.M.

    Published 2020
    “…In this paper, a firefly algorithm based hybrid algorithm through retaining global convergence of firefly algorithm and ability to generate connected topologies of optimality criteria (OC) method is proposed as an alternative method to solve stress-based topology optimization problems. …”
    Get full text
    Get full text
    Article
  4. 4

    Firefly analytical hierarchy algorithm for optimal allocation and sizing of distributed generation in radial distribution network by Bujal, Noor Ropidah

    Published 2022
    “…The AHP was also found to yield accurate weights of the coefficient factors for each objective function compared to the weight-sum method generally used in studies. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  5. 5

    Optimal location and size of distributed generation to reduce power losses and improve voltage profiles using differential evolution optimization method by Hammadi, Ahmed Sahib

    Published 2016
    “…Some existing algorithms need to be improved while others, need to add a new parameter for improving the performance of optimization methods and making it more effective and efficient. …”
    Get full text
    Get full text
    Thesis
  6. 6

    Optimal Power Flow of power systems using Harris Hawks Optimization and Salp Swarm Algorithm by Zohrul, Islam Mohammad

    Published 2021
    “…Additionally, the proposed methods solved multi-objective OPF problem with the help of no preference weighted sum method. …”
    Get full text
    Get full text
    Thesis
  7. 7

    Optimal Location And Sizing Of Distrubuted Generator Using PSO And GA Algorithms In Power Systems by Hassan, Ayat Saleh

    Published 2019
    “…Some existing algorithms need to be improved while others, need to add a new parameter for improving the performance of optimization methods and making it more effective and efficient. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  8. 8

    Solving the integrated inventory supply chain problems using meta-heuristic methods / Seyed Mohsen Mousavi by Seyed Mohsen , Mousavi

    Published 2018
    “…A Modified Particle Swarm Optimization (MPSO) algorithm, a Genetic Algorithm (GA), a modified fruit fly optimization algorithm (MFOA) and a simulated annealing (SA) algorithm were used to find the optimal solution. …”
    Get full text
    Get full text
    Get full text
    Thesis
  9. 9
  10. 10
  11. 11
  12. 12

    Empowering Energy-Sustainable IoT Devices With Harvest Energy-Optimized Deep Neural Networks by Alzahrani, Saeed, Salh, Adeb, Audah, Lukman, A. Alhartomi, Mohammed, Alotaibi, Abdulaziz, Alsulami, Ruwaybih

    Published 2024
    “…This paper applied the proposed Optimal Transmit Power and PS Ratio (OTPR) algorithm to maximize the EE for SWIPT based on the partial derivative of Lagrange dual decomposition methods. …”
    Get full text
    Get full text
    Get full text
    Article
  13. 13

    Development an accurate and stable range-free localization scheme for anisotropic wireless sensor networks by Han, Fengrong

    Published 2022
    “…The localization accuracy and robustness of comparison indicated that the developed DWGWO-DV-Hop algorithm super outperforms the other classical range-free methods. …”
    Get full text
    Get full text
    Thesis
  14. 14
  15. 15

    Inversion of 2D and 3D DC resistivity imaging data for high contrast geophysical regions using artificial neural networks / Ahmad Neyamadpour by Neyamadpour, Ahmad

    Published 2010
    “…By comparing the common non-linear least square inversion methods (i.e., the steepest descent method, the nonlinear conjugate gradients method, Newton-type methods and smoothness-constrained least squares methods), the L1_ norm smoothness-constrained optimization method (or robust inversion technique) has been recognized as the most efficient of the least squares methods mentioned here, because it sometimes gives relatively better results in high resistivity zones with sharp boundaries. …”
    Get full text
    Get full text
    Thesis
  16. 16

    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
  17. 17

    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
  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