Search results for: ARTIFICIAL NEURAL NETWORK, MODELLING,SHIP SPEED, ENGINE FUEL CONSUMPTION - Bridge of Knowledge

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Search results for: ARTIFICIAL NEURAL NETWORK, MODELLING,SHIP SPEED, ENGINE FUEL CONSUMPTION

Search results for: ARTIFICIAL NEURAL NETWORK, MODELLING,SHIP SPEED, ENGINE FUEL CONSUMPTION

  • Energy Systems Stations, W, ET, sem.7, zimowy 22/23 (PG_00042106)

    e-Learning Courses
    • R. Liberacki

    Internal combustion engines - principle of operation and classification. Heat balance of the engine. Uniform and combined propulsion systems.The main comonents of the propulsion system. Power plant efficiency and waste heat utilization. Cooling water system, lubricating oil system, fuel oil systeml, gaseos fuel system (LNG), compressed air system, exhaust gas system. Fittings and accessories of pipeline systems in the power plant....

  • Mathematical and numerical modelling, L, IDE, sem. 01, summer 21/22,(M:00057379)

    e-Learning Courses
    • K. J. Kaliński

    Modelling. Optimal control. Modal analysis. High speed milling. Mechatronic design.

  • Fuel, Oils and Greases, W, E, sem.01, zimowy 22/23

    e-Learning Courses

    Division and origin of fuels. Fossil energy resources in Poland and in the world. Production and structure of fuel consumption. Main directions of crude oil processing. Classification and physical properties of gaseous and liquid fuels - natural gas, gasoline, kerosene, diesel oil, heating oil. Classification and characteristic indicators of solid fuels - hard coal, lignite, peat. Fuel contaminants and methods of their removal....

  • Deep Learning Basics 2023/24

    e-Learning Courses
    • K. Draszawka

    A course about the basics of deep learning intended for students of Computer Science. It includes an introduction to supervised machine learning, the architecture of basic artificial neural networks and their training algorithms, as well as more advanced architectures (convolutional networks, recurrent networks, transformers) and regularization and optimization techniques.

  • Fuel, Oils and Greases, W, E, sem.03, zimowy 22/23

    e-Learning Courses
    • P. Bzura

    Division and origin of fuels. Fossil energy resources in Poland and in the world. Production and structure of fuel consumption. Main directions of crude oil processing. Classification and physical properties of gaseous and liquid fuels - natural gas, gasoline, kerosene, diesel oil, heating oil. Classification and characteristic indicators of solid fuels - hard coal, lignite, peat. Fuel contaminants and methods of their removal....

  • Technology and Energy Conversion Machines - Nowy

    e-Learning Courses
    • D. Stepanenko

    The course covers the basics of mechanical, electrical and thermal energy production in industry and maritime transport. Describes installations supporting high-power engines. Particular attention has been paid to the fuel systems of internal combustion engines. The treatment of engine exhaust gases is described.

  • Technology and Energy Conversion Machines - Nowy kopiuj 1

    e-Learning Courses
    • Z. Kneba

    The course covers the basics of mechanical, electrical and thermal energy production in industry and maritime transport. Describes installations supporting high-power engines. Particular attention has been paid to the fuel systems of internal combustion engines. The treatment of engine exhaust gases is described.

  • Technology and Energy Conversion Machines

    e-Learning Courses
    • Z. Kneba

    The course covers the basics of mechanical, electrical and thermal energy production in industry and maritime transport. Describes installations supporting high-power engines. Particular attention has been paid to the fuel systems of internal combustion engines. The treatment of engine exhaust gases is described.

  • Deep neural networks for data analysis 24/25

    e-Learning Courses
    • J. Cychnerski
    • K. Draszawka

    This course covers introduction to supervised machine learning, construction of basic artificial deep neural networks (DNNs) and basic training algorithms, as well as the overview of popular DNNs architectures (convolutional networks, recurrent networks, transformers). The course introduces students to popular regularization techniques for deep models. Besides theory, large part of the course is the project in which students apply...

  • Mathematical and numerical modelling,W,IDE-EMSS,IIst,sem.01,lato,2023/24 (PG_00057379)

    e-Learning Courses
    • K. J. Kaliński

    Modelling of controlled mechanical systems by the mixed method of rigid and flexible finite elements: The finite element volume problems. Dynamics of multibody systems. Modelling of stationary closed loop systems. Modelling of systems whose configuration changes with time. Modelling of nonlinear controlled systems. Optimal control at energy performance index: Control of continuous nonstationary systems in domain of generalised...

  • Mathematical and Numerical Modelling, L, IDE IInd, sem.01, summer, 2022/23(00057379)

    e-Learning Courses
    • K. J. Kaliński

    Modelling of controlled mechanical systems by the mixed method of rigid and flexible finite elements: The finite element volume problems. Dynamics of multibody systems. Modelling of stationary closed loop systems. Modelling of systems whose configuration changes with time. Modelling of nonlinear controlled systems. Optimal control at energy performance index: Control of continuous nonstationary systems in domain of generalised...