自然科学版 英文版
自然科学版 英文版
自然科学版 英文版

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中南大学学报(英文版)

Journal of Central South University

Vol. 13    No. 4    August 2006

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A new approach to predicting mining induced surface subsidence
DING De-xin(丁德馨)1,2, ZHANG Zhi-jun(张志军)1,2, BI Zhong-wei(毕忠伟)1,2

1. School of Resources and Safety Engineering, Central South University, Changsha 410083, China;
2. School of Architectural, Resources and Environment Engineering,
Nanhua University, Hengyang 421001, China

Abstract:There are many parameters influencing mining induced surface subsidence. These parameters usually interact with one another and some of them have the characteristic of fuzziness. Current approaches to predicting the subsidence cannot take into account of such interactions and fuzziness. In order to overcome this disadvantage, many mining induced surface subsidence cases were accumulated, and an artificial neuro fuzzy inference system(ANFIS) was used to set up 4 ANFIS models to predict the rise angle, dip angle, center angle and the maximum subsidence,
respectively. The fitting and generalization prediction capabilities of the models were tested. The test results show that the models have very good fitting and generalization prediction capabilities and the approach can be applied to predict the mining induced surface subsidence.

 

Key words: mining induced surface subsidence; fuzziness and interaction of parameters; artificial neural fuzzy inference system

中南大学学报(自然科学版)
  ISSN 1672-7207
CN 43-1426/N
ZDXZAC
中南大学学报(英文版)
  ISSN 2095-2899
CN 43-1516/TB
JCSTFT
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