Thermal Science - scientific journal [ keyword: artificial neural networks ]

THERMAL SCIENCE

International Scientific Journal

[ keyword: artificial neural networks ]

Papers published in THERMAL SCIENCE also containing keyword artificial neural networks

Experimental and artificial neural network approach for forecasting of traffic air pollution in urban areas: The case of Subotica

THERMAL SCIENCE, volume 14, Supplement 1, YEAR 2010

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PM10, meteorological parameters, forecasting PM10 concentrations, artificial neural networks

Modeling of photovoltaic modules using a gray-box neural network approach

THERMAL SCIENCE, volume 21, Issue 6, YEAR 2017

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photovoltaic module, artificial neural networks, Gray-Box model, output power, data clustering, functional approximator

Analysis and modeling of the effects of process parameters on specific cutting energy in abrasive water jet cutting

THERMAL SCIENCE, volume 22, Supplement 5, YEAR 2018

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specific cutting energy, abrasive water jet cutting, modeling, artificial neural networks, aluminum alloy

Multilayer method for solving a problem of metals rupture under creep conditions

THERMAL SCIENCE, volume 23, Supplement 2, YEAR 2019

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сreep, fracture, parameter identification, the Cauchy problem, ODE, artificial neural networks, multilayer neural networks

Using artificial neural network for predicting heat transfer coefficient during flow boiling in an inclined channel

THERMAL SCIENCE, volume 25, Issue 5, YEAR 2021

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inclined channel, flow boiling, heat transfer coefficient, artificial neural networks

Machine-learning based thermal conductivity prediction of propylene glycol solutions: Real time heat propagation approach

THERMAL SCIENCE, volume 27, Issue 4, YEAR 2023

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artificial neural networks, classification, Temperature Profiles, thermal conductivity, heat transfer

Rapid prediction of solid rocket ignition transient process using artificial neural networks

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Solid Rocket Motor, Ignition Transient, Quasi-One Dimensional Model, machine learning, artificial neural networks

The possibility of modeling agricultural biomass ash by neural networks concerning proximate analysis inputs

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biomass, artificial neural networks, proximate analysis, ash content, modelling