Application of an artificial neural network (ANN) simulator to increase the operational efficiency of a roadheader.

ABSTRACT: Mining machine simulators involve an IT system based on dedicated software to represent a specific piece of hardware in the working environment of operators, service technicians, and people supervising the operation. In this study, a proprietary roadheader simulator was used to simulate the machine's operating parameters and its dynamic behavior during the mining process in changing conditions. The information collected from the simulation was subsequently fed to a model and analyzed using artificial neural networks (ANN) to enable learning and predictive features regarding the simulated roadheader. This article presents the findings that led to the development of an ANN structure to determine the values of 15 parameters based on four input signals. The ANN models are multilayer perceptron

SUBMITTER: Cheluszka P 

PROVIDER: S-EPMC12835196 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature