Optimization study of intelligent decision-making system for coal processing plant based on big data analysis

Abstract

Optimizing the intelligent decision-making system of coal processing plants is better to improve the economic efficiency of coal processing plants and realize the high-quality development of coal processing plants. In this paper, an integrated intelligent decision-making platform for a coal processing plant is constructed based on big data technology, and the intelligent data analysis techniques of the platform are optimized by using an improved whale optimization algorithm and BP neural network. Examples analyze the optimized crude coal slurry and flotation systems’ processes, and the economic benefits are analyzed. From the optimization of the crude coal slurry sorting system, the ash content in the 0.25mm particle size region was reduced from 55.37% to 13.12%, and the ash content in the −0.125mm particle size region was reduced from 42.68% to 15.96%. From the flotation system optimization, when the flotation time increases from 120s to 180s, the ash content increases from 16.27% to 17.19%, and then to 240s, the ash content increases to 19.44%. Using the integrated intelligent decision-making platform can achieve a net increase in revenue of 4,276,800 yuan for the crude coal slurry sorting system and a net increase of 11,274,200 yuan for the flotation system. This shows that the integrated intelligent decision-making platform can improve the coal processing plant’s quality and efficiency and promote intelligent production.

Keywords

• intelligent decision-making platform
• whale optimization algorithm
• bp neural network
• coal processing plant
• system optimization.
• 68t05