Search Results - (( parallel optimization sensor algorithm ) OR ( processes optimization _ algorithm ))

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  1. 1

    Simulated kalman filter (SKF) based image template matching for distance measurement by using stereo vision system by Nurnajmin Qasrina Ann, Ayop Azmi

    Published 2018
    “…That is why, image template matching problem is now considered as an optimization problem. By implementing optimization algorithm in image template matching, it is expected that the computation time can be reduced. …”
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  2. 2

    Online teleoperation of writing manipulator through graphics processing unit based accelerated stereo vision by Abu Raid, Fadi Imad Osman

    Published 2021
    “…These algorithms are then parallelized using Compute Unified Device Architecture CUDA C language to run on Graphics Processing Unit GPU for hardware acceleration. …”
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  3. 3

    DC-based PV-powered home energy system by Sabry, Ahmad H.

    Published 2017
    “…The system can be managed via a central computer which attains the energy data via only one remote XBee RF wireless node which is processing the sensors measurement of the system components. …”
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  4. 4

    Single-objective and multi-objective optimization algorithms based on sperm fertilization procedure / Hisham Ahmad Theeb Shehadeh by Hisham Ahmad, Theeb Shehadeh

    Published 2018
    “…The obtained results are compared with the results of four algorithms. These algorithms are Genetic Algorithms (GA), Parallel Genetic Algorithm (PGA), Particle Swarm Optimization (PSO) and Accelerated Particle Swarm Optimization (APSO). …”
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  5. 5
  6. 6

    Estimation of core size distribution of magnetic nanoparticles using high-Tc SQUID magnetometer and particle swarm optimizer-based inversion technique by Mohd Mawardi, Saari, Mohd Herwan, Sulaiman, Kiwa, Toshihiko

    Published 2023
    “…In this work, the core size estimation technique of magnetic nanoparticles (MNPs) using the static magnetization curve obtained from a high-Tc SQUID magnetometer and a metaheuristic inversion technique based on the Particle Swarm Optimizer (PSO) algorithm is presented. The high-Tc SQUID magnetometer is constructed from a high-Tc SQUID sensor coupled by a flux transformer to sense the modulated magnetization signal from a sample. …”
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  7. 7

    A Novel Hybrid Harris Hawk-Arithmetic Optimization Algorithm for Industrial Wireless Mesh Networks by Devan, P.A.M., Ibrahim, R., Omar, M., Bingi, K., Abdulrab, H.

    Published 2023
    “…The HHAOA algorithm was evaluated on various benchmark functions and compared with other optimization algorithms, namely Arithmetic Optimization Algorithm, Moth Flame Optimization, Sine Cosine Algorithm, Grey Wolf Optimization, and Harris Hawk Optimization. …”
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  8. 8

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

    Published 2018
    “…In this paper, three optimization algorithms which are particle swarm optimization (PSO), gravitational search, and Sine Cosine algorithms are employed to optimize the grinding process parameters that may either reduce the cost, increase the productivity or obtain the finest surface finish and resulting a higher grinding process performance. …”
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  9. 9

    A refined differential evolution algorithm for improving the performance of optimization process by A. R., Yusoff, Nafrizuan, Mat Yahya

    Published 2011
    “…However, the population trapped in local optimality and premature convergence to cause in DE algorithm have cause poor performance during optimization process. …”
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  10. 10

    A comparative study on testing optimization techniques with combinatorial interaction testing for optimizing software product line testing by Maidin, Nur Farrahin, Hassan, Sa’Adah, Baharom, Salmi, Md. Sultan, Abu Bakar

    Published 2025
    “…An experiment has been conducted on the most commonly used optimization algorithms in previous studies. The optimization algorithms we explored are the Genetic Algorithm, Cuckoo Search algorithm, Ant Colony algorithm, and Particle Swarm Optimization algorithm. …”
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  11. 11

    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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  12. 12

    Stochastic process and tutorial of the African buffalo optimization by Odili, Julius Beneoluchi, Noraziah, Ahmad, Alkazemi, Basem, Zarina, M.

    Published 2022
    “…This paper presents the data description of the African buffalo optimization algorithm (ABO). ABO is a recently-designed optimization algorithm that is inspired by the migrant behaviour of African buffalos in the vast African landscape. …”
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  13. 13

    On the optimal control of the steel annealing processes as a two-stage hybrid systems via PSO algorithms by Arumugam, M.S., Murthy, G.R., Loo, C.K.

    Published 2009
    “…The heating and soaking furnaces of the steel annealing line form the two-stage hybrid systems. Three algorithms including particle swarm optimisation (PSO) with globally and locally tuned parameters (GLBest PSO), a parameter free PSO algorithm (pf-PSO) and a PSO-like algorithm via extrapolated PSO (ePSO) are considered to solve this optimal control problem for the two-stage steel annealing processes (SAP). …”
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  14. 14

    Process Planning Optimization In Reconfigurable Manufacturing Systems by Musharavati, Farayi

    Published 2008
    “…Therefore, this study explores how to model reconfigurable manufacturing activities in an optimization perspective and how to develop and select appropriate non-conventional optimization techniques for reconfigurable process planning.In this study, a new approach to modeling Manufacturing Process Planning Optimization (MPPO) was developed by extending the concept of manufacturing optimization through a decoupled optimization method. …”
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  15. 15

    Stochastic process and tutorial of the African bufalo optimization by Odili, Julius Beneoluchi, Noraziah, Ahmad, Alkazemi, Basem Y., M., Zarina

    Published 2022
    “…This paper presents the data description of the African buffalo optimization algorithm (ABO). ABO is a recently-designed optimization algorithm that is inspired by the migrant behaviour of African buffalos in the vast African landscape. …”
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  16. 16

    Simulated Kalman Filter algorithms for solving optimization problems by Nor Hidayati, Abdul Aziz

    Published 2019
    “…Optimization is an important process in solving most engineering problems. …”
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  17. 17

    Adaptable algorithms for performance optimization of dynamic batch manufacturing processes by Teo, Kenneth Tze Kin

    Published 2018
    “…This study aims to explore the potential of implementing a multi-objective dynamic optimizer to acquire regular optimization on nonlinear characteristic of batch manufacturing process. …”
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  18. 18

    Optimization of micro-end milling process parameters of titanium alloy using non-dominated sorting genetic algorithm by Golshan, Abolfazl

    Published 2013
    “…Finally, non-dominated sorting genetic algorithm-II as evolutionary optimization approach was used for multi-objective optimization of the micro-end milling process. …”
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  19. 19

    Optimization of Electrical Discharge Machining Process by Metaheuristic Algorithms by Zainal, Nurezayana, Sithambranathan, Mohanavali, Khattak, Umar Farooq, Mohd Zain, Azlan, A. Mostafa, Salama, Mat Deris, Ashanira

    Published 2024
    “…Several attempts have been carried out to solve the optimization problem involved in the EDM process. This paper emphasizes optimizing the EDM process using three metaheuristic algorithms: Glowworm Swarm Optimization (GSO), Grey Wolf Optimizer (GWO), and Whale Optimization Algorithm (WOA). …”
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  20. 20

    Optimization of physical vapour deposition coating process parameters using genetic algorithm by Mohammad Jarrah, Mu'ath Ibrahim

    Published 2014
    “…In order to get output result, the three parameters were used to develop a polynomial quadratic equation that was designed using response surface methodology (RSM). Then, in order to optimize the coating process parameters, genetic algorithms (GAs) were used for the optimization work. …”
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