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5 ta ish

Ish: Artificial neural network hyperparameters optimization for predicting the thermal conductivity of MXene/graphene nanofluids

  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. 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

  3. An intelligent multi-objective decision framework for geothermal–LNG assisted co-generation of power, natural gas, and hydrogen

    Bhishma Karki, Dessalegn Ahmed Yeshanew, Ilkhom Khaydarov +7

    MaqolaHybrid Renewable Energy SystemsInternational Communications in Heat and Mass Transfer20260 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