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Работы, на которые ссылается эта работа

Работ: 84

Работа: Accurate prediction of the rheological behavior of MWCNT-Al2O3/water-ethylene glycol nanofluid with metaheuristic-optimized machine learning models

  1. Enhancing Thermal Conductivity of Fluids With Nanoparticles

    Stephen U. S. Choi

    Статья1995Цитирований: 33
    ABI

  2. Particle swarm optimization

    James Kennedy, R.C. Eberhart

    Статья2002Цитирований: 15
    ABI

  3. Multilayer feedforward networks are universal approximators

    Kurt Hornik, Maxwell B. Stinchcombe, Halbert White

    Статья1989Цитирований: 8
    ABI

  4. The Viscosity of Concentrated Suspensions and Solutions

    H. Brinkman

    Статья1952Цитирований: 7
    ABI

  5. Summarizing multiple aspects of model performance in a single diagram

    Karl E. Taylor

    Статья2001Цитирований: 6
    ABI

  6. Pareto optimal design of a finned latent heat thermal energy storage unit using a novel hybrid technique

    Hamid Maleki, Mehdi Ashrafi, Nastaran Zandy Ilghani +2

    Статья2021Цитирований: 6
    ABI

  7. A review on genetic algorithm: past, present, and future

    Sourabh Katoch, Sumit Singh Chauhan, Vijay Kumar

    Обзорная статья2020Цитирований: 5
    ABI

  8. Optimization of thermophysical properties of nanofluids using a hybrid procedure based on machine learning, multi-objective optimization, and multi-criteria decision-making

    Tao Zhang, Anahita Manafi Khajeh Pasha, S. Mohammad Sajadi +5

    Статья2024Цитирований: 5
    ABI

  9. Insights into water-lubricated transport of heavy and extra-heavy oils: Application of CFD, RSM, and metaheuristic optimized machine learning models

    Mishal Alsehli, Ali Basem, Dheyaa J. Jasim +7

    Статья2024Цитирований: 5
    ABI

  10. Artificial neural network hyperparameters optimization for predicting the thermal conductivity of MXene/graphene nanofluids

    Yunyan Shang, Karrar A. Hammoodi, As’ad Alizadeh +7

    Статья2024Цитирований: 5
    ABI

  11. Optimizing Gaussian process regression (GPR) hyperparameters with three metaheuristic algorithms for viscosity prediction of suspensions containing microencapsulated PCMs

    Tao Hai, Ali Basem, As’ad Alizadeh +7

    Статья2024Цитирований: 5
    ABI

  12. Integrating artificial neural networks, multi-objective metaheuristic optimization, and multi-criteria decision-making for improving MXene-based ionanofluids applicable in PV/T solar systems

    Tao Hai, Ali Basem, As’ad Alizadeh +8

    Статья2024Цитирований: 5
    ABI

  13. Marine Predators Algorithm: A nature-inspired metaheuristic

    Afshin Faramarzi, Mohammad Heidarinejad, Seyedali Mirjalili +1

    Статья2020Цитирований: 4
    ABI

  14. Combining artificial intelligence and computational fluid dynamics for optimal design of laterally perforated finned heat sinks

    Seyyed Amirreza Abdollahi, Ali Basem, As’ad Alizadeh +5

    Статья2024Цитирований: 4
    ABI

  15. A Review on Nanofluids: Preparation, Stability Mechanisms, and Applications

    Wei Yu, Huaqing Xie

    Обзорная статья2011Цитирований: 3
    ABI

  16. Thermal Conductivity of Nanoparticle - Fluid Mixture

    Xinwei Wang, Xianfan Xu, Stephen U. S. Choi

    Статья1999Цитирований: 3
    ABI

  17. PEARSON VERSUS SPEARMAN, KENDALL'S TAU CORRELATION ANALYSIS ON STRUCTURE-ACTIVITY RELATIONSHIPS OF BIOLOGIC ACTIVE COMPOUNDS

    Lorentz Jäntschi, Sorana D. Bolboacă, Iuliu Haţieganu

    Статья2005Цитирований: 3
    ABI

  18. Some Comments on the Evaluation of Model Performance

    Cort J. Willmott

    Статья1982Цитирований: 3
    ABI

  19. Smart modeling by using artificial intelligent techniques on thermal performance of flat‐plate solar collector using nanofluid

    Milad Sadeghzadeh, Mohammad Hossein Ahmadi, Mostafa Kahani +3

    Статья2019Цитирований: 3
    ABI

  20. A well-trained artificial neural network for predicting the rheological behavior of MWCNT–Al2O3 (30–70%)/oil SAE40 hybrid nanofluid

    Mohammad Hemmat Esfe, S. Ali Eftekhari, Maboud Hekmatifar +1

    Статья2021Цитирований: 3
    ABI

  21. RETRACTED: Rheological behavior of hybrid MWCNTs-TiO2/EG nanofluid: A comprehensive modeling and experimental study

    Shu‐Rong Yan, Rasool Kalbasi, Quyen Nguyen +1

    Статья2020Цитирований: 2
    ABI

  22. Integrating artificial Intelligence-Based metaheuristic optimization with Machine learning to enhance Nanomaterial-Containing latent heat thermal energy storage systems

    Ali Basem, Hanaa Kadhim Abdulaali, As’ad Alizadeh +6

    Статья2024Цитирований: 2
    ABI

  23. Без названия

    ДругоеЦитирований: 2
    ABI

  24. Determining the best structure for an artificial neural network to model the dynamic viscosity of MWCNT-ZnO (25:75)/SAE 10W40 oil nano-lubricant

    Mohammad Hemmat Esfe, S. Ali Eftekhari, S. Mohammad Sajadi +3

    Статья2023Цитирований: 2
    ABI

  25. Без названия

    ДругоеЦитирований: 2
    ABI