Three environmental parameters, i.e. dust concentrations, dust dispersion, and free silica content, were introduced into the traditional indices of the neural network model in order to construct a new prediction index and explore a new method for preventing the incidence of pneumoconiosis with intelligent accuracy and universality. Data of the pneumoconiosis patients from Huabei Mining Group (HBMG) of China from 1980 to 2017 were collected. SPSS22.0 was used to develop the combined models based on Back Propagation (BP) neural network model, Radial Basis Function (RBF) neural network model, and Multiple Linear Regression (MLR) model. The paired sample t-test was performed between the real and predicted values. According to this model, it was predicted that 382 coal workers in HBMG were likely to suffer from pneumoconiosis in 2022 and the incidence rate was 4.48%. It is necessary to take prevention measures and transfer these workers from their current positions. In four combined models, the BP-MLR combined model achieved the optimal error parameters and the most accurate prediction. This study provided a scientific basis for effective control and prevention of the incidence of the pneumoconiosis.

At present, the world is committed to the development of environmentally friendly, sustainable and industrial safety. The effective treatment of industrial solid waste can be applied in the field of industrial safety. It is one of the ways to apply industrial solid waste to industrial safety to modify industrial solid waste and combine active powder to prepare industrial solid waste-based composite powder explosion inhibitors and apply it to underground coal dust explosion. This paper introduces the modification and preparation methods of industrial solid waste, and analyzes the good explosion suppression effect and good economic benefit of industrial solid waste-based composite powder explosion inhibitors on coal dust explosion. In this paper, four kinds of industrial solid wastes (red mud, slag, fly ash and sludge) were modified, and the modified solid waste materials with good carrier characteristics were obtained. Combined with a variety of active powders (NaHCO₃, KH₂PO₄ and Al(OH)₃), the industrial solid waste-based composite powder explosion inhibitors were obtained by solvent-crystallization (WCSC) and dry coating by ball milling (DCBM). Those kinds of explosion inhibitors can suppress the explosion of pulverized coal in 40–50% of cases. Compared with the powder explosion inhibitor commonly used in industry, it has a lower production cost and better explosion suppression effect. Those kinds of explosion inhibitors have a good industrial application prospect.