Search Results - (( parallel distribution factor algorithm ) OR ( pressure optimization method algorithm ))

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  1. 1

    Algorithm development for optimization of a refrigeration system by Izzat, Mohamad Adnan

    Published 2010
    “…This thesis deals with algorithm development for optimization of a refrigeration system. …”
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    Undergraduates Project Papers
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    Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm by Al-Jumaili A.H.A., Muniyandi R.C., Hasan M.K., Singh M.J., Paw J.K.S., Al-Jumaily A.

    Published 2025
    “…Parallel power loads anomalies are processed by a fast-density peak clustering technique that capitalizes on the hybrid strengths of Canopy and K-means algorithms all within Apache Mahout's distributed machine-learning environment. …”
    Article
  3. 3

    Investigation on the dynamic of computation of semi autonomous evolutionary computation for syntactic optimization of a set of programming codes by Mohammad Sigit Arifianto, Tze, Kenneth Kin Teo, Liau, Chung Fan, Liawas Barukang, Zaturrawiah Ali Omar

    Published 2007
    “…Genetic Algorithm as one of the Evolutionary Computation method improve the execution of parallel programming codes by optimizing the number of processors and the distribution of data. …”
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    Research Report
  4. 4

    Metaheuristic Algorithm for Wellbore Trajectory Optimization by Biswas, K., Vasant, P.M., Vintaned, J.A.G., Watada, J.

    Published 2019
    “…In drilling engineering, the optimization of wellbore plays an important role, which can be optimized based on minimization of length, mud pressure, critical pressure, etc. …”
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    Conference or Workshop Item
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    Improved black-winged kite algorithm and finite element analysis for robot parallel gripper design by Haohao, Ma, As’arry, Azizan, Yanwei, Feng, Lulu, Cheng, Delgoshaei, Aidin, Ismail, Mohd Idris Shah, Ramli, Hafiz Rashidi

    Published 2024
    “…The Good Point Set (GPS), nonlinear convergence factor, and adaptive t-distribution method improve BKA, which enhances exploration and exploitation performance, convergence speed, and solution quality. …”
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    Article
  7. 7

    Improvement and application of particle swarm optimization algorithm by Deevi, Durga Praveen, Kodadi, Sharadha, Allur, Naga Sushma, Dondapati, Koteswararao, Chetlapalli, Himabindu, Perumal, Thinagaran

    Published 2025
    “…Finally, real-world tests are performed to verify the proposed Algorithm's efficacy compared to existing optimization methods. …”
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    Article
  8. 8

    Numerical simulation of fluid flow in three dimensional domain based on two stage pressure-velocity correction method by Sabir, O., Ya, T.M.Y.S.T.

    Published 2015
    “…In this paper a two stage pressure-velocity correction approach for immersed boundary method is proposed. …”
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    Conference or Workshop Item
  9. 9

    Numerical simulation of fluid flow in three dimensional domain based on two stage pressure-velocity correction method by Sabir, O., Ya, T.M.Y.S.T.

    Published 2015
    “…In this paper a two stage pressure-velocity correction approach for immersed boundary method is proposed. …”
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    Conference or Workshop Item
  10. 10

    Impact of evolutionary algorithm on optimization of nonconventional machining process parameters by B V, Raghavendra, R Annigiri, Anandkumar, Srikatamurthy, JS

    Published 2025
    “…Using a Python environment, three evolutionary algorithms such as, Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Firefly Algorithm (FA), were simulated to evaluate their effectiveness in minimizing surface roughness (Ra). …”
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    Article
  11. 11

    Thin Film Roughness Optimization In The Tin Coatings Using Genetic Algorithms by Fauzi, Nur Faiqah, Mohamad Jaya, Abdul Syukor, Mohammad Jarrah, Mu’ath Ibrahim, Akbar, Habibullah

    Published 2017
    “…In order to represent the process variables and coating roughness, a quadratic polynomial model equation was developed. Genetic algorithms were used in the optimization work of the coating process to optimize the coating roughness parameters. …”
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    Article
  12. 12

    PID Tuning Of Process Plant Using Evolutionary Algorithm by Guong, Robert Ling Leh

    Published 2014
    “…In this project, Evolutionary algorithm (Particle Swarm Optimization) is implemented to optimize the controller parameters in order to improve the system performance of the real pressure plant. …”
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    Final Year Project
  13. 13

    Design and analysis of management platform based on financial big data by Chen, Yuhua, Mustafa, Hasri, Zhang, Xuandong, Liu, Jing

    Published 2023
    “…In addition, a financial data management platform based on distributed Hadoop architecture is designed, which combines MapReduce framework with the fuzzy clustering algorithm and the local outlier factor (LOF) algorithm, and uses MapReduce to operate in parallel with the two algorithms, thus improving the performance of the algorithm and the accuracy of the algorithm, and helping to improve the operational efficiency of enterprise financial data processing. …”
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    Article
  14. 14

    Base pressure control through micro jets at supersonic Mach numbers using experimental and machine learning approach by Aabid, Abdul, Khan, Sher Afghan, Yasir, Javed

    Published 2026
    “…Furthermore, machine learning (ML) algorithms were utilized to predict base pressure outcomes and optimize control strategies. …”
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    Article
  15. 15

    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. …”
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    Thesis
  16. 16

    CFD-based optimization of base pressure behavior on suddenly expanded flows at supersonic Mach numbers by Jaimon, Dennis Quadros, Khan, Sher Afghan, Prashanth, T.

    Published 2022
    “…Furthermore, to assess the right range of conditions for maximizing base pressure, the genetic algorithm (GA), desirability function approach (DFA), and particle swarm optimization (PSO) techniques were implemented. …”
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    Article
  17. 17

    Enhancing solid oxide fuel cell efficiency through advanced model identification using differential evolutionary mutation fennec fox algorithm by Singla, Manish Kumar, Gupta, Jyoti, Kumar, Ramesh, Jangir, Pradeep, Louzazni, Mohamed, Giri, Nimay Chandra, Al Gburi, Ahmed Jamal Abdullah, EI‑Kenawy, E. I.‑Sayed M., Alharbi, Amal H.

    Published 2025
    “…An ideal model should be adaptable to varying operating pressures and temperatures. This research introduces a novel approach for optimal SOFC model identification using a differential evolutionary mutation Fennec fox algorithm (DEMFFA). …”
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    Article
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    Modeling And Optimization Of Physical Vapour Deposition Coating Process Parameters For Tin Grain Size Using Combined Genetic Algorithms With Response Surface Methodology by Mohamad Jaya, Abdul Syukor, Muhamad, Mohd Razali, Abd Rahman, Md Nizam, Mohammad Jarrah, Mu'ath Ibrahim, Hasan Basari, Abd Samad

    Published 2015
    “…Optimization of thin film coating parameters is important in identifying the required output.Two main issues of the process of physical vapor deposition (PVD) are manufacturing costs and customization of cutting tool properties.The aim of this study is to identify optimal PVD coating process parameters.Three process parameters were selected, namely nitrogen gas pressure (N2),argon gas pressure (Ar),and Turntable Speed (TT),while thin film grain size of titanium nitrite (TiN) was selected as an output response.Coating grain size was characterized using Atomic Force Microscopy (AFM) equipment.In this paper,to obtain a proper output result,an approach in modeling surface grain size of Titanium Nitrite (TiN)coating using Response Surface Method (RSM) has been implemented. …”
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    Article