Search Results - (( parameters variation research algorithm ) OR ( parameter optimization method algorithm ))

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  1. 1

    Enhanced gravitational search algorithm for nano-process parameter optimization problem / Norlina Mohd Sabri by Mohd Sabri, Norlina

    Published 2020
    “…Based on the capabilities of the metaheuristic algorithms, this research is proposing the enhanced Gravitational Search Algorithm (eGSA) to solve the nano-process parameter optimization problem. …”
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    Thesis
  2. 2

    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
    “…The implementation of Particle Swarm Optimization (PSO) algorithm in optimizing Proportional-Integral-Derivative (PID) controller's parameters is a popular technique to improve the performance of a control system. …”
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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
    “…The implementation of Particle Swarm Optimization (PSO) algorithm in optimizing Proportional-Integral-Derivative (PID) controller's parameters is a popular technique to improve the performance of a control system. …”
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    Book Section
  4. 4

    A modified technique in RFID networking planning and optimization by Nawawi, Azli

    Published 2015
    “…To reduce the complexity of the optimization process, this research focuses on developing a method to determine the optimum setting for PSO parameters. …”
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    Thesis
  5. 5

    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
    “…Several researchers have reported different optimization methods for blade parameters such as Blade Element Momentum theory (BEM), Computational Fluid Dynamics (CFD) and Supervisory Control and Data Acquisition (SCADA) system. …”
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    Thesis
  6. 6

    Recent Evolutionary Algorithm Variants for Combinatorial Optimization Problem by Anniza, Hamdan, San Nah, Sze, Say Leng, Goh, Kang Leng, Chiew, Wei King, Tiong

    Published 2023
    “…Hybridization in evolutionary algorithm mechanisms such as initialization methods, local searches, specific design operators, and self-adaptive parameters enhance the algorithm’s performance. …”
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    Article
  7. 7

    Optimal Parameters of Rectifier Power Transformer by Intelligent Techniques by K.S., Rama Rao, K.N.Md., Hasan, Karsiti, M. N.

    Published 2009
    “…Two stochastic methods for locating global minimum and optimal design parameters of a rectifier power transformer, by Genetic Algorithm (GA) and Simulated Annealing (SA) are presented. …”
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    Citation Index Journal
  8. 8

    Optimal Parameters of Rectifier Power Transformer by Intelligent Techniques by Kondapalli, K. S. Rama Rao, K., K. N. Md Hasan, M, M. N. Karsiti

    Published 2009
    “…Abstract-Two stochastic methods for locating global minimum and optimal design parameters of a rectifier power transformer, by Genetic Algorithm (GA) and Simulated Annealing (SA) are presented. …”
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    Citation Index Journal
  9. 9

    CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING by ISLAM, BADAR UL ISLAM

    Published 2017
    “…In the hybrid scheme, the initial parameters of the modified BP neural network are optimized by using the global search ability of genetic algorithm, improved by cat chaotic mapping to enrich its optimization capability. …”
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    Thesis
  10. 10

    Application of Multi-objective Genetic Algorithm (MOGA) for design optimization of valve timing at various engine speeds by Mohiuddin, A. K. M., Rahman, Mohammed Ataur, Haw Shin, Yap

    Published 2011
    “…This paper aims to demonstrate the effectiveness of Multi-Objective Genetic Algorithm Optimization and its practical application on the automobile engine valve timing where the variation of performance parameters required for finest tuning to obtain the optimal engine performances. …”
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    Article
  11. 11

    A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

    Published 2024
    “…Given the multitude of components to manage, streamflow forecasting is preferable to employ an algorithm with low sensitivity to parameter variations. …”
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    Thesis
  12. 12

    Design optimization of valve timing at various engine speeds using Multi-Objective Genetic Algorithm (MOGA) by Mohiuddin, A. K. M., Ashour, Ahmed Aly Ibrahim Shaaban, Yap, Haw Shin

    Published 2008
    “…This paper aims to demonstrate the effectiveness of Multi- Objective Genetic Algorithm Optimization and its robust practical application on the automobile engine valve timing where the variation of performance parameters required for finest tuning to obtain the optimal engine performances. …”
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    Proceeding Paper
  13. 13

    Water level forecasting using feed forward neural networks optimized by African Buffalo Algorithm (ABO) by Ahmed, Ehab Ali

    Published 2019
    “…Weakness such as trapped in local minima, slow convergence and finding a good rate between exploitation and exploration of the search space. This research proposed a swarm intelligence training algorithm, Improved African Buffalo Optimization algorithm (IABO) based on the Metaheuristic method called the African Buffalo Optimization algorithm (ABO). …”
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    Thesis
  14. 14

    Optimization and Decomposition Methods in Network Traffic Prediction Model: A Review and Discussion by Jinmei Shi, Yu-Beng Leau, Kun Li, Yong, Jin Park, Zhiwei Yan

    Published 2020
    “…This article discusses past network traffic prediction research and critically examines the optimization and decomposition technologies used in the model, lists the model parameter structure based on the research methodology, the data set used, the evaluation criteria and so on. …”
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    Article
  15. 15

    To develop an efficient variable speed compressor motor system by Mohd. Yatim, Abdul Halim, Mulyo Utomo, Wahyu

    Published 2007
    “…To achieve a robust controller from variation of motor parameters, a real-time or on-line learning algorithm based on a second order optimization Levenberg-Marquardt is employed. …”
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    Other
  16. 16

    Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources by Kumar, A., Ridha, S., Narahari, M., Ilyas, S.U.

    Published 2021
    “…The detailed parametric analysis exhibits the competency of the proposed algorithm to explain the rheological features. Monte-Carlo simulation is performed by propagating uncertainty to investigate the dominant parameters affecting simulated results. …”
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    Article
  17. 17

    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 training data required to train the two-metamodeling techniques were generated using a verified nonlinear finite element algorithm developed in the current research. The algorithm is based on the updated Lagrangian formulation, which takes into consideration geometrical, material nonlinearity, and contact. …”
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    Thesis
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    Development of cell formation algorithm and model for cellular manufacturing system by Nouri, Hossein

    Published 2011
    “…Therefore, for this proposes good benchmarked algorithm, bacteria foraging algorithm is selected and developed to solve multiobjective cell formation model and traced constraints satisfaction handling to produce feasible optimal solution. …”
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    Thesis
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