Construction of Intelligent Mining Visualization Centralized Control System Based on Neural Network and Genetic Algorithm

Accelerating the iterative upgrade of mine intelligent equipment provides strong technical support for the construction of smart mines, and at the same time, safe production forces mining enterprises to carry out the construction of smart mines. Due to the limitation of underground geological conditions and the nonlinear characteristics of surrounding environment, the parameters to be monitored on each working face are quite complicated and isolated from each other. The traditional data processing method has great limitations, and the quantitative model will make it difficult to determine parameters, reduce system performance and coordinate. Focusing on the establishment of multi-source data model of mining business and the correlation of model data, this paper constructs an intelligent monitoring model based on genetic algorithm (GA) optimized neural network, and studies the visual application effect of centralized control platform on mining production data with the help of digital twin visual integration technology. The simulation results show that the algorithm in this paper has remarkable prediction ability, good real-time performance, powerful learning function and high accuracy. The proposed intelligent mining visualization model can monitor various mine parameters, realize real-time graphic visualization, scene and real-time interaction of mine data, and improve the management level and work efficiency of mining enterprises.