Title :
Optimizing Model of Blasting Parameters Based on Fuzzy Neural Network
Author :
Ye, Haiwang ; Wang, Yang ; Chang, Jian ; Liu, Fang ; Yao, Peng
Author_Institution :
Sch. of Resources & Environ. Eng., Wuhan Univ. of Technol., Wuhan, China
Abstract :
Because of the complexity and polytropism of rock and the complexity of blasting proceeding, it is very difficult to obtain better blasting parameters with a certain way. In order to gain perfect blasting effects expected by designers, blasting engineers have been studying the optimizing of blasting parameters all the time. The intelligent optimizing model of blasting parameters based on fuzzy neural network is set up in this paper. The input parameters of the model are rock properties and blasting requirements, and the outputs are the properties of explosive, blasting parameters, initiation means and charging structure. When a new set of parameters are input into the model trained by some successful examples, a good output will be gotten very easily. At last, the optimizing model is applied to a cement mine. From the application, a conclusion can be drawn that it is feasible and reliable to carry out blasting design with the optimizing model based on fuzzy neural network.
Keywords :
explosions; fuzzy neural nets; mining; rocks; blasting engineer; blasting parameter optimization; blasting requirement; cement mine; charging structure; explosive; fuzzy neural network; rock polytropism; rock properties; Design engineering; Design optimization; Explosives; Fuzzy neural networks; Information security; Intelligent networks; Neural networks; Powders; Shape; Takagi-Sugeno model;
Conference_Titel :
Multimedia Information Networking and Security, 2009. MINES '09. International Conference on
Conference_Location :
Hubei
Print_ISBN :
978-0-7695-3843-3
Electronic_ISBN :
978-1-4244-5068-8
DOI :
10.1109/MINES.2009.32