ARTIFICIAL NEURAL NETWORK – A TOOL FOR OPTIMISING MINING PARAMETERS
In many circumstances, our fundamental understanding of soil and rock behavior still falls short of being able to predict how the ground will behave. Cause-wise analysis of mine accidents reveals that roof falls continue to remain the single largest killer. Ground control operation is an ‘imprecise’ area of engineering due to the fact that we are dealing with a material produced by nature (the ground). Under these circumstances, expert judgement plays an important role, and empirical approaches to design are widely used. Thus,such accidents can be obviated using the accurate measurement, optimization and analysis of data a predictions based on previous results using one of the Artificial Intelligence technique i.e. Neural Networking. It is a simple computational model, which is analogous to that of neural system in human brain. In this paper we have given a brief study on Neural Network Technology including Back Propagation Neural Network (BPNN) to train the network for optimization the mine support parameters. Some of the variable parameters associated with the underground excavation work have been taken as input/output parameter for the network. The technique of simulation of the result has also been discussed .
mine support parameters optimisation Neural Network
Sudhir kumar Kashyap D.R.Parhi Amlendu Sinha
CIMFR, Barwa Road, Dhanbad – 826015( INDIA) N.I.T. Rourkela – 769008 ( INDIA)
国际会议
香港
英文
1-6
2009-05-19（万方平台首次上网日期，不代表论文的发表时间）