Mp-Matt:a Time Series Prediction Method with Mine Gas Sensor Data
Weihan Wang · Journal of Physics Conference Series · 2020
Abstract Based on the Encoder-Decoder Framework, Combined with the Pooling Preprocessing and the Mupli-Attention Mechanism, This Paper Proposed the Mp-Matt Model for the Prediction of Mine Gas Time Series Data. the Model Had a Good Predictive Accuracy in the Data Set of Oxygen, Carbon Monoxide and Methane in a Mine. the Accuracy of the Best Baseline Comparison Model Had Increased by 10.30%, 22.26% and 20.02%, Respectively. This Study Compared the Effects of Each Component in the Model. the Comparison Showed That the Multi-Attention Layer Had the Most Obvious Effect. the Increase of the Metic Pooling Layer Was Lower, and the Effect of Adding the Fatt Layer Was Slightly Better Than That of Adding the Hatt Layer.