Neural network modelling studies of steam oxidised kinetic behaviour of advanced steels and Ni-based alloys at 800 °C for 3000 h

Characteristics of the Evolution of Carbide Morphology in the Haynes® 230® Alloy as a Result of High Temperature Annealing

“…The material examined was the heat-resistant Ni-based alloy Haynes ® 230 ® ; its chemical composition is shown in Table 1. (Dudziak et al 2017a(Dudziak et al , 2017b(Dudziak et al , 2018. In this type of steam oxidation test set-up, 100% pure steam was generated by pumping deionized water from a reservoir placed underneath the furnace.…”

Data fusion based on‐line product quality evaluation of ternary cathode material cyber‐physical systems

“…When weighing variables, the Pearson correlation between the input variables and the output variables is calculated according to (16), for the different dimensions of the input variables. The input variables are assigned with different weights by (17) r…”

“…For process non-linearity, which occurs in the manufacture of ternary cathode material, is another problem to be considered in the TCM-CPS. Researchers investigated methods such as least squares support vector machine (LSSVM) [15,16], neural network [17][18][19], and non-linear kernel technique [20,21]. Integrating the mechanism and process data, Chen et al [22] proposed a modelling method, which was applied to establish a model for roller kiln of ternary cathode material.…”

Artificial neural network modelling to predict the efficiency of aluminium sacrificial anode

“…The choice of activation function depends on the specific problem being solved and the architecture of the ANN. These novel approaches to corrosion prediction utilising ANN have led to significant advances in this field Some research has been done on the simulation of corrosion in different environments based on neural networks [9][10][11][12]. Hu et al tried to predict the polarisation curves of Ni-Cr-Mo-V steel in environments such as seawater using a neural network [13].…”