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A new approach to predicting mining induced surface subsidence 被引量:4

A new approach to predicting mining induced surface subsidence
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摘要 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. 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.
出处 《Journal of Central South University of Technology》 EI 2006年第4期438-444,共7页 中南工业大学学报(英文版)
基金 Project(50274043) supported by the National Natural Science Foundation of China project (01JJY1004) supported bythe Natural Science Foundation of Hunan Province project (01A015) supported by the Natural Science Foundation of Hunan ProvincialEducation Committee
关键词 地表下沉 采矿 模糊神经网络 地表压力 mining induced surface subsidence fuzziness and interaction of parameters artificial neural fuzzy inference system
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