where 𝑟 𝑐 ̅ and 𝑟 𝑅 ̅ are the vectors of the compound and reaction rates. Secondly, the ANN model of the rate expression is split into two parts. The first part is a feedforward neural network where inputs are partial pressure of components, and the second one is the Arrhenius-type expression for temperature dependence of rates. The second part represents a neural network layer with exponential activation function that is applied in the CRNN . 'Arrhenius' temperature 𝑇 𝑚 as input for this layer was used and is defined as: