Spatial-temporal digital twin models as a direction for the development of cross-cutting digital technologies

Abstract

The proposed spatial-time digital twin model is based on a neural network approach for solving partial differential equations characterizing a physical object. The model aims to develop cross-cutting digital technologies. This approach makes it possible to account newly received data and thereby maintain the relevance of the model. The approach allows integrating the knowledge of specialists and engineers for solving a number of important tasks. The model uses machine learning and is therefore adaptive. Keywords—digital twin; neural network solution; machine learning; fire system.