Search Results - (( java implementation bat algorithm ) OR ( parameters variation function algorithm ))

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  1. 1

    Fuzzy modeling using Bat Algorithm optimization for classification by Noor Amidah, Ahmad Sultan

    Published 2018
    “…A Sazonov Engine which is a fuzzy java engine is use to apply Bat Algorithm in the experiment. …”
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    Undergraduates Project Papers
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    Design of low order quantitative feedback theory and H-infinity-based controllers using particle swarm optimisation for a pneumatic actuator system by Ali, Hazem I.

    Published 2010
    “…On the other hand, the design of conventional control with structured and unstructured uncertainties is also presented. The PSO algorithm is used to minimize the infinity norm of the transfer function of the nominal closed loop system to obtain the optimal parameters of the weighting functions. …”
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    Thesis
  3. 3

    Performance of particle swarm optimization under different range of direct current motor's moment of inertia / Mohd Azri Abdul Aziz by Abdul Aziz, Mohd Azri

    Published 2018
    “…However, the use of moment of inertia and other parameters of DC motor are mostly to complete the transfer function and no specific analysis was done on the effects of their variations to the control method. …”
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    Thesis
  4. 4

    Performance of particle swarm optimization under different range of direct current motor's moment of inertia / Mohd Azri Abdul Aziz by Abdul Aziz, Mohd Azri

    Published 2018
    “…However, the use of moment of inertia and other parameters of DC motor are mostly to complete the transfer function and no specific analysis was done on the effects of their variations to the control method. …”
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    Book Section
  5. 5

    Performance evaluation of smoothed functional algorithm based methods for sigmoid-PID control optimization in MIMO twin-rotor systems by Mok, Ren Hao, Mohd Ashraf, Ahmad

    Published 2024
    “…This paper explores the tuning of the Sigmoid Proportional-Integral-Derivative (SPID) controller using variations of the Smoothed Functional Algorithm (SFA) for the underactuated Multiple-Input Multiple-Output (MIMO) twin-rotor system. …”
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    Conference or Workshop Item
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    The PID controller parameter tuning based on a modified differential evolutionary optimization algorithm for the intelligent active vibration control of a combined single link robo... by Moloody, Abbas, As’arry, Azizan, Hong, Tang Sai, Raja Kamil, ., Zolfagharian, Ali

    Published 2025
    “…This research suggests an evolutionary algorithm that incorporates the variational techniques mentioned above, which will be combined by a certain ratio, and the specific computational procedure. …”
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    Article
  9. 9

    Model-based hybrid variational level set method applied to lung cancer detection by Jing, Wang, Liew, Siau-Chuin, Azian, Abd Aziz

    Published 2024
    “…This algorithm simplifies the (Local Intensity Clustering) LIC model and devises a new energy functional based on the region-based pressure function. …”
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    Article
  10. 10

    Identifying and estimating solar cell parameters using an enhanced slime mould algorithm by Logeswaary, Devarajah, Mohd Ashraf, Ahmad, Jui, Julakha Jahan

    Published 2024
    “…Second, the tangent hyperbolical function of the formula p in the original SMA was replaced with an exponential function to create more variations for selecting the updated equation. …”
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    Article
  11. 11

    Fast and optimal tuning of fractional order PID controller for AVR system based on memorizable-smoothed functional algorithm by Ren Hao, Mok, Ahmad, Mohd Ashraf

    Published 2022
    “…Therefore, this study proposes a modified smoothed function algorithm (MSFA) based method to tune the FOPID controller of AVR system since it requires fewer number of function evaluation per iteration. …”
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    Article
  12. 12

    Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar by Md. Rasel, Sarkar

    Published 2019
    “…There have two most uses activation function namely tansig and logsig. The essence of this study is that it compares the effect of activation functions (tansig and logsig) in the performance of time series forecasting since activation function is the core element of any artificial neural network model. …”
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    Thesis
  13. 13

    Variational Bayesian inference for exponentiated Weibull right censored survival data by Jibril Abubakar, Jibril Abubakar, Mohd Asrul Affendi Abdullah, Mohd Asrul Affendi Abdullah, Oyebayo Ridwan Olaniran, Oyebayo Ridwan Olaniran

    Published 2023
    “…The results from the experiments reveal that the Variational Bayesian (VB) approach is better than the competing Metropolis-Hasting Algorithm and the reference maximum likelihood estimates.…”
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    Article
  14. 14

    The effect of adaptive parameters on the performance of back propagation by Abdul Hamid, Norhamreeza

    Published 2012
    “…The Back Propagation algorithm or its variation on Multilayered Feedforward Networks is widely used in many applications. …”
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    Thesis
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    Design Optimization of 3-Phase Rectifier Power Transformers by Genetic Algorithm and Simulated Annealing by K.S., Rama Rao, Md Hasan, Khairul Nisak

    Published 2008
    “…A discussion on the limitations and variation of GA parameters while minimizing the single and multi-objective functions satisfying the performance constraints on the proposed optimal design concludes the paper.…”
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    Citation Index Journal
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    Identification of continuous-time model of hammerstein system using modified multi-verse optimizer by Most. Julakha, Jahan Jui

    Published 2021
    “…Numerical and experimental results are analyzed to focus on the convergence curve of the fitness function, the parameter variation index, frequency and time domain response and the Wilcoxon rank test. …”
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    Thesis
  18. 18

    Model-based hybrid variational level set method applied to object detection in grey scale images by Wang, Jing

    Published 2024
    “…To tackle the persistent challenge of segmenting grayscale images with both uneven characteristics and high noise levels, a hybrid level-set algorithm based on kernel metrics is introduced. This algorithm leverages an improved multi-scale mean filter to mitigate grayscale inhomogeneity while reducing the impact of scale parameter selection. …”
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    Thesis
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    Neural Network Model and Finite Element Simulation of Spring back in Plane-Strain Metallic Beam Bending by Abu Khadra, Fayiz Y. M.

    Published 2006
    “…The second function predicts the punch displacement for a given material, geometrical parameters, and the bend angle after springback. …”
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    Thesis