Prediction of blast induced ground vibrations and frequency in opencast mine: A neural network approach

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.     

PBIB设计的约化

设Ｄ是一个有ｍ个结合类的ＰＢＩＢ设计，且它的参数λ１，λ２，．．．，λｍ中至少有两个是相等，第二节中，给出了ＰＢＩＢ设计Ｄ可以用遂次合并结合类来约化的充分必要条件，第三节给出了ＰＢＩＢ设计Ｄ可以用同时合并结合来约化的充分必要条件，最后，在第四节里我们研究了上述两种方法之间的关系。     

CONSTRUCTION OF PBIB DESIGNS BY USING DESCARTES PRODUCT OF KNOWN PBIB DESIGNS

The author discuss the Descartes product of a number of association schemes, introduce the Descartes product of t(t \geq 2) given PBIB designs and, finally, solve the general problem: How to obtain a new PBIB design from any t(t \geq 2) PBIB designs?