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5 ta ish

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

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

    Yi Ru, Ali B.M. Ali, Karwan Hussein Qader +5

    MaqolaNanofluid Flow and Heat TransferInternational Journal of Thermal Sciences20251 iqtibos
    ABI

  2. Prediction of the thermophysical properties of Ag-reduced graphene oxide-water/ethylene-glycol hybrid nanofluids using different machine learning methods

    Huaguang Li, Ali B.M. Ali, Rasha Abed Hussein +6

    MaqolaNanofluid Flow and Heat TransferCase Studies in Thermal Engineering20250 iqtibos
    ABI

  3. Intelligent design of lithium-ion battery thermal management systems for electric vehicles: Integration of gene expression programming modeling and multi-objective atomic orbital search optimization

    Hangxin Liu, Ahmad Alkhayyat, Normurot Fayzullaev +7

    MaqolaAdvanced Battery Technologies ResearchJournal of Power Sources20260 iqtibos
    ABI

  4. Integration of ANN tuned by the chameleon swarm algorithm and multi-objective besiege and conquer algorithm for emission and performance optimization of diesel/methanol engines

    Biju Theruvil Sayed, Zyad Shaaban, Hamad AlMohamadi +7

    MaqolaAdvanced Combustion Engine TechnologiesInternational Communications in Heat and Mass Transfer20260 iqtibos
    ABI

  5. Intelligent design of latent heat storage systems with bio-inspired branched vascular fins using a hybrid framework integrating PSO/IGWO-ANN, multi-objective sunflower optimization, and the COPRAS method

    Chou‐Yi Hsu, Biju Theruvil Sayed, Yosuef Alotaibi +7

    MaqolaGreenhouse Technology and Climate ControlInternational Communications in Heat and Mass Transfer20260 iqtibos
    ABI