A new approach to predicting mining induced surface subsidence

De-xin Ding , Zhi-jun Zhang , Zhong-wei Bi

Journal of Central South University ›› 2006, Vol. 13 ›› Issue (4) : 438 -444.

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Journal of Central South University ›› 2006, Vol. 13 ›› Issue (4) : 438 -444. DOI: 10.1007/s11771-006-0064-y
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A new approach to predicting mining induced surface subsidence

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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.

Keywords

mining induced surface subsidence / fuzziness and interaction of parameters / artificial neural fuzzy inference system

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De-xin Ding,Zhi-jun Zhang,Zhong-wei Bi. A new approach to predicting mining induced surface subsidence. Journal of Central South University, 2006, 13(4): 438-444 DOI:10.1007/s11771-006-0064-y

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