Data Processing of Atmospheric Dust Concentration Based on Neural Network

A major problem in the detection of fine dust is that the calculation of the relationship between the number concentration and the mass concentration is too complicated and the particle distribution in each place is different. It is difficult to find a unified calculation method. Based on the above considerations, this topic proposes a neural-network-based atmospheric dust concentration data processing system design, which enables the neural network to learn autonomously to explore the relationship between the two concentrations in order to achieve the results of the mass concentration measurement device for the calculation of number concentrations. This system is mainly composed of data measurement module and data processing module. On the basis of completing the overall design, a data processing platform based on a neural network is built to achieve a targeted solution to specific problems. The experimental results show that the system can effectively analyze and process the measurement data, meet the original design function requirements, and verify the correctness of the system design program.