Mine Gas Wireless Monitoring and Forecasting Network Based on Support Vector Machine

Zhen Bi Li; Yuan Yuan Jiang; Wei Zhu

doi:10.4028/www.scientific.net/AMR.424-425.232

Paper Titles

The Relationship between Freeway Safety and Geometric Design Elements
p.215

Optimization Research on Cyclic Waterflooding in Low Permeability Fractured Reservoir
p.220

A Novel Fusion Algorithm of Visible Image and Infrared Image Based on NSCT
p.223

Traffic Throttling to Improve TCP Incast Throughput
p.227

Mine Gas Wireless Monitoring and Forecasting Network Based on Support Vector Machine
p.232

Design of Multi-Sensor Communication System of Wheelchair Robot Base on the CANopen
p.236

Analysis to Effective Elastic Modulus and Porosity for Artificial Bone Scaffold with Hydroxyapatite Microspheres
p.241

Protein Folding Simulation Based on Improved Simulated Annealing Algorithm
p.246

Modeling and Analysis of Metabolism Process with Finite State Machine
p.250

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 424-425Mine Gas Wireless Monitoring and Forecasting...

Mine Gas Wireless Monitoring and Forecasting Network Based on Support Vector Machine

Abstract:

Gas monitoring is considered as the most important mean in the safe production of coalmine. Time delay inevitably exists in the current gas monitoring technology widely used today. This research uses Support vector machine to forecast gas concentration. ZigBee wireless network protocol is adopted so that a wireless gas monitoring network with concentration predicting function is obtained. In this way the present time delay in Gas concentration monitoring will be improved and the scope of monitoring will be expanded at the same time

You might also be interested in these eBooks

Advanced Research on Engineering Materials, Energy, Management and Control

View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 424-425)

Pages:

232-235

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.424-425.232

Citation:

Cite this paper

Online since:

January 2012

Authors:

Zhen Bi Li, Yuan Yuan Jiang, Wei Zhu

Keywords:

Gas Concentration Prediction, Support Vector Machine (SVM), Wireless Monitor Network, ZigBee

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Wang, Y, Zhang, Z., Li, C.J.: Wireless Sensor Network Applied to Coal Mine Gas Monitoring and Measuring System. Coal Science and Technology. 2007, 06（35）: 34-36. (in Chinese).

Google Scholar

[2] RUAN, D. X, TANG, D.F., ZHANG, X.G.: Application of Zigbee Based Wireless Sensor Network in Underground Coal Mine Environment. Coal Mine Machinery. 2008, 29（6）: 163-164. (in Chinese).

Google Scholar

[3] DENG, N.Y., TIAN, Y.G.: Support Vector Machine- Theory, Algorithms and Expand. BEIJIN: Science Press, 2009. (in Chinese).

Google Scholar

[4] HU, W.L.: Prediction Modeling Based on Bayes Support Vector Machine. Journal of Beijing University of Aeronautics and A. 2010, 36（4）: 486-489. (in Chinese).

Google Scholar

[5] ZHOU, H.L.,: Combination of Support Vector Machine and Evidence Theory in Information Fusion. 2008, 09（21）: 1566-1570. (in Chinese).

Google Scholar

[6] XU, Z., MAO, Z.Z.: Incremental Learning of Support Vector Machine Based on Hyperspheres. 2010, 1（31）: 16-20. (in Chinese).

Google Scholar