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10 ta ish

Ish: IMPROVING THE INTENSITY OF THE STEELMAKING TECHNOLOGICAL PROCESS BASED ON FUZZY LOGIC

  1. Forecasting electricity consumption by LSTM neural network

    V. Ya. Ushakov, Ikromjon U. Rakhmonov, Numon N. Niyozov +1

    MaqolaEnergy Load and Power ForecastingBulletin of the Tomsk Polytechnic University Geo Assets Engineering202324 iqtibos
    ABI

  2. Mathematical modeling of minimization of electricity consumption by industrial enterprises with continuous production

    Ikromjon U. Rakhmonov, V. Ya. Ushakov, Aysulu M. Najimova +2

    MaqolaDiverse Industrial Engineering TechnologiesBulletin of the Tomsk Polytechnic University Geo Assets Engineering202410 iqtibos
    ABI

  3. The comparative analysis of electrode control systems of electric arc furnaces and ladle furnaces

    А. А. Николаев, P. G. Tulupov, G. V. Astashova

    Maqola20163 iqtibos
    ABI

  4. Back-propagation fuzzy system as nonlinear dynamic system identifiers

    L.-X. Wang, Jerry M. Mendel

    Maqola20032 iqtibos
    ABI

  5. Electric arc current control for an electric arc furnace based on fuzzy logic

    Loredana Ghiormez, Octavian Proștean

    Maqola20152 iqtibos
    ABI

  6. Curve-fitting-based method for modeling voltage–current characteristic of an ac electric arc furnace

    Yu‐Jen Liu, G. W. Chang, Rong-Chin Hong

    Maqola20092 iqtibos
    ABI

  7. The Electrodes Positioning Control System for the Electric Arc Furnace Basing on Fuzzy Logic

    Yaroslav Paranchuk, Y. V. Shabatura, Oleksiy Kuznyetsov

    Maqola20212 iqtibos
    ABI

  8. Modelling and Control of Electrode System for an Electric Arc Furnace

    Maqola20142 iqtibos
    ABI

  9. Sarlavhasiz

    Boshqa1 iqtibos
    ABI

  10. Sarlavhasiz

    Boshqa1 iqtibos
    ABI