Title: Prediction of blast induced ground vibrations and frequency in opencast mine: A neural network approach
Abstract: This paper presents the application of neural network for the prediction of ground vibration and frequency by all possible influencing parameters of rock mass, explosive characteristics and blast design. To investigate the appropriateness of this approach, the predictions by ANN is also compared with conventional statistical relation. Network is trained by 150 dataset with 458 epochs and tested it by 20 dataset. The correlation coefficient determined by ANN is 0.9994 and 0.9868 for peak particle velocity (PPV) and frequency while correlation coefficient by statistical analysis is 0.4971 and 0.0356.
Publication Year: 2005
Publication Date: 2005-06-23
Language: en
Type: article
Indexed In: ['crossref']
Access and Citation
Cited By Count: 259
AI Researcher Chatbot
Get quick answers to your questions about the article from our AI researcher chatbot