Title :
Model of gas warning system based on neural network expert
Author :
Peng Hong ; Li Lei-jun ; Li Yun-jie
Author_Institution :
Fac. of Electr. & Control Eng., Liaoning Tech. Univ., Huludao, China
Abstract :
Large number of coal mines in China, the repeated occurrence of gas accidents, which take the great loss to the people´s lives and property. In recent years, early-warning model of gas become more and more popular by many people. The key is early warning of gas access to the various characteristics of gas, in-depth analysis, and then make the appropriate warning. This paper discusses a new type of gas early warning model. First, the neural network and expert system combined with a new type of neural network expert system as the core of the model, and then design a specific gas early warning.
Keywords :
accident prevention; alarm systems; coal; expert systems; mining industry; natural gas technology; neural nets; coal mines; early-warning model; gas access; gas accidents; gas early warning model; gas warning system; in-depth analysis; neural network expert system; Accidents; Alarm systems; Artificial neural networks; Computer networks; Control engineering; Design engineering; Expert systems; Knowledge acquisition; Neural networks; Quantization; early warning; expert system; gas; neural network;
Conference_Titel :
Computer Design and Applications (ICCDA), 2010 International Conference on
Conference_Location :
Qinhuangdao
Print_ISBN :
978-1-4244-7164-5
Electronic_ISBN :
978-1-4244-7164-5
DOI :
10.1109/ICCDA.2010.5541397