Search Results - (( _ distribution new algorithm ) OR ( parameter optimization isotherm algorithm ))

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  1. 1

    Performance assessment of Sn-based lead-free solder composite joints based on extreme learning machine model tuned by Aquila optimizer by Temitope T., Dele-Afolabi, Masoud, Ahmadipour, Mohamed Ariff, Azmah Hanim, A.A., Oyekanmi, M.N.M., Ansari, Sikiru, Surajudeen, Kumar, Niraj

    Published 2024
    “…An extreme learning machine (ELM) prediction approach refined by Aquila optimizer (AO), a new cutting-edge metaheuristic optimization algorithm was utilized to develop a prediction model for the performance assessment of the developed solder composites. …”
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  2. 2

    Performance assessment of Sn-based lead-free solder composite joints based on extreme learning machine model tuned by Aquila optimizer by Dele-Afolabi T.T., Ahmadipour M., Azmah Hanim M.A., Oyekanmi A.A., Ansari M.N.M., Sikiru S., Kumar N.

    Published 2025
    “…An extreme learning machine (ELM) prediction approach refined by Aquila optimizer (AO), a new cutting-edge metaheuristic optimization algorithm was utilized to develop a prediction model for the performance assessment of the developed solder composites. …”
    Article
  3. 3

    Effective adsorption of metolachlor herbicide by MIL-53(Al) metal-organic framework: Optimization, validation and molecular docking simulation studies by Ahmad Isiyaka, H., Jumbri, K., Soraya Sambudi, N., Uba Zango, Z., Ain Fathihah Binti Abdullah, N., Saad, B.

    Published 2022
    “…The optimization by the RSM was significant with minimum number of experimental runs, lesser error and showed a simultaneous interaction of the adsorption parameters in predicting MET adsorption capacity. …”
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  4. 4

    Effective adsorption of metolachlor herbicide by MIL-53(Al) metal-organic framework: Optimization, validation and molecular docking simulation studies by Ahmad Isiyaka, H., Jumbri, K., Soraya Sambudi, N., Uba Zango, Z., Ain Fathihah Binti Abdullah, N., Saad, B.

    Published 2022
    “…The optimization by the RSM was significant with minimum number of experimental runs, lesser error and showed a simultaneous interaction of the adsorption parameters in predicting MET adsorption capacity. …”
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  5. 5

    Performance of amidoxime-modified poly(acrylonitrile- Co-acrylic acid) for removal of boron in aqueous solution by Lau, Kia Li

    Published 2019
    “…The best fit model for adsorption isotherm was Sips model with heterogeneity factor (n) = 0.7611. …”
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  6. 6

    Ancestral dynamic voting algorithm for mutual exclusion in partitioned distributed systems by Zarafshan, Faraneh, Karimi, Abbas, Al-Haddad, Syed Abdul Rahman, Saripan, M. Iqbal, Subramaniam, Shamala

    Published 2013
    “…In this study, a new dynamic algorithm is presented as a solution for mutual exclusion in partitioned distributed systems. …”
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  7. 7

    Optimizations and docking simulation study for metolachlor adsorption from water onto MIL-101(Cr) metal�organic framework by Isiyaka, H.A., Jumbri, K., Sambudi, N.S., Zango, Z.U., Abdullah, N.A.F.B., Saad, B.

    Published 2022
    “…The adsorption kinetics and isotherm models show the presence of multilayer adsorption and chemisorption controlled adsorption process. …”
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  8. 8

    Optimizations and docking simulation study for metolachlor adsorption from water onto MIL-101(Cr) metal�organic framework by Isiyaka, H.A., Jumbri, K., Sambudi, N.S., Zango, Z.U., Abdullah, N.A.F.B., Saad, B.

    Published 2022
    “…The adsorption kinetics and isotherm models show the presence of multilayer adsorption and chemisorption controlled adsorption process. …”
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  9. 9

    Optimizations and docking simulation study for metolachlor adsorption from water onto MIL-101(Cr) metal�organic framework by Isiyaka, H.A., Jumbri, K., Sambudi, N.S., Zango, Z.U., Abdullah, N.A.F.B., Saad, B.

    Published 2022
    “…The adsorption kinetics and isotherm models show the presence of multilayer adsorption and chemisorption controlled adsorption process. …”
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    Article
  10. 10

    A new technique for the reconfiguration of radial distribution network for loss minimization by Shamsudin, Nur Hazahsha, abidullah, Noor Athira, Abdullah, Abdul Rahim, Sulaima, Mohamad Fani, Jaafar, Hazriq Izzuan

    Published 2014
    “…In this paper, a new technique called as Improved Genetic Algorithm (IGA) for reconfiguring distribution network simultaneously implemented with the placement of small scale power generation or Distributed Generation (DG) is presented. …”
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  11. 11

    Modelling and simulation of hollow profile aluminium extruded product by Sulaiman, Shamsuddin, Baharudin, B. T. Hang Tuah, Mohd Ariffin, Mohd Khairol Anuar, Magid, Hani Mizhir

    Published 2015
    “…This process is an isothermal process with an extrusion ratio of 3.3. Subsequently, the optimized algorithm for these extrusion parameters was suggested based on the simulation results. …”
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    Modeling and simulation of forward Al extrusion process using FEM by Magid, Hani Mizhir, Sulaiman, Shamsuddin, Mohd Ariffin, Mohd Khairol Anuar, Baharudin, B. T. Hang Tuah

    Published 2014
    “…Optimized algorithms for extrusion parameters were proposed regarding the concluded simulating results. …”
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  14. 14

    A new efficient checkpointing algorithm for distributed mobile computing by Mansouri, Houssem, Badache, Nadjib, Aliouat, Makhlouf, Pathan, Al-Sakib Khan

    Published 2015
    “…Considering this issue, the contribution in this paper is a proposal of a new checkpointing algorithm suitable for mobile computing systems. …”
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  15. 15

    Optimal location and size estimation of distributed generators by employing grouping particle swarm optimization and grouping genetic algorithm by Mohammed, Zahraa Abdulkareem

    Published 2017
    “…This work is aimed to decrease the total real and reactive power losses while enhancing the voltage profile of the distribution network with less computation time by proposing two new artificial intelligence algorithms, i.e. grouping particle swarm optimization algorithm and grouping genetic algorithm. …”
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    Modeling of Cu(II) adsorption from an aqueous solution using an Artificial Neural Network (ANN) by Khan, T., Manan, T.S.B., Isa, M.H., Ghanim, A.A.J., Beddu, S., Jusoh, H., Iqbal, M.S., Ayele, G.T., Jami, M.S.

    Published 2020
    “…The Fletcher-Reeves conjugate gradient backpropagation (BP) algorithm was the best fit among all of the tested algorithms (mean squared error (MSE) of 3.84 and R2 of 0.989). …”
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  20. 20

    Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets by Saeed, Sana

    Published 2019
    “…A new self-adaptive hybrid algorithm (CSCMAES) is introduced for optimization. …”
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