Computer Engineering and Applications ›› 2011, Vol. 47 ›› Issue (10): 244-248.

• 工程与应用 •

### Study on gas concentration prediction based on chaotic time series

ZHANG Baoyan1，2，LI Ru2，3，MU Wenyu2

1. 1.College of Computer Science and Technology，Jinzhong University，Jinzhong，Shanxi 030600，China
2.School of Computer & Information Technology，Shanxi University，Taiyuan 030006，China
3.Key Lab of Computational Intelligence and Chinese Information Processing of MOE，Shanxi University，Taiyuan 030006，China
• Received:1900-01-01 Revised:1900-01-01 Online:2011-04-01 Published:2011-04-01

### 基于混沌时间序列的瓦斯浓度预测研究

1. 1.晋中学院 计算机科学与技术学院，山西 晋中 030600
2.山西大学 计算机与信息技术学院，太原 030006
3.山西大学 计算智能与中文信息处理教育部重点实验室，太原 030006

Abstract: In recent years，mine disasters are occuring frequently，especially gas accidents which are often reported in newspapers.Gas accidents are usually accompanied by a high concentration of the gas，so gas concentration predicting of the future moment is an effective means of gas accident forecasting and has very important significance to production safety in coal mines.This paper simplifies C-C method on chaos theory，and reconstructs phase space using time series of gas concentration values by monitoring from five coal mines.The paper chooses an appropriate value for the delay time and the embedding dimension according to the real values of gas concentration，and then forecasts the gas concentration of the next moment using weight one-rank local-region method.The experimental results show time series?of gas concentration have obviously the chaotic property.The results also show moderate calculation and better forecast results when the length of time series is 500.The mean square error of forecast results of 100 abnormal gas concentration values is 0.122 024，thus the method can be used for the prediction of gas accidents and provide basis for decision making in coal mines，for example，taking measures such as ventilationin in a timely manner.