| Genetic Programming Approach for Predicting Surface Subsidence Induced by Mining |
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| 作者姓名： | 翟淑花 高谦 宋建国 |
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| 作者单位： | Department of Civil Engineering University of Science and Technology Beijing Beijing 100083 China，Department of Civil Engineering University of Science and Technology Beijing Beijing 100083 China Key Laboratory of Ministry of Education on High Efficient and Safety Mining for Metal Mines Beijing 100083 China，Department of Civil Engineering University of Science and Technology Beijing Beijing 100083 China |
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| 基金项目： | This paper is supported by Jinchuan Group Ltd.(No.2004-01D). |
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| 摘 要： | INTRODUCTIONThe study of surface subsidence resulting fromunderground mining holds significance in view ofbeneficial effects on national economy and people’sliving conditions.As is known,a large quantity ofminerals need to be exploited for modernization con-struction.Mining leads to surface subsidence,someunderground engineering and production facilities aredestroyed accordingly,which blocks the developmentof production and retards people’s living standard.To solve this contradiction,su…
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| 关 键 词： | 遗传规划方法 矿山 沉降 地质条件 |
| 收稿时间： | 2006-06-28 |
| 修稿时间： | 2006-09-25 |
Genetic Programming Approach for Predicting Surface Subsidence Induced by Mining |
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| Zhai Shuhua,Gao Qian,Song Jianguo.Genetic Programming Approach for Predicting Surface Subsidence Induced by Mining[J].Journal of China University of Geosciences,2006,17(4):361-366. |
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| Authors: | Zhai Shuhua Gao Qian Song Jianguo |
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| Institution: | 1. Department of Civil Engineering,University of Science and Technology Beijing,Beijing 100083,China
2. Department of Civil Engineering,University of Science and Technology Beijing,Beijing 100083,China;Key Laboratory of Ministry of Education on High Efficient and Safety Mining for Metal Mines,Beijing 100083,China |
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| Abstract: | The surface subsidence induced by mining is a complex problem, which is related with many complex and uncertain factors. Genetic programming (GP) has a good ability to deal with complex and nonlinear problems, therefore genetic programming approach is proposed to predict mining induced surface subsidence in this article. First genetic programming technique is introduced, second, surface subsidence genetic programming model is set up by selecting its main affective factors and training relating to practical engineering data, and finally, predictions are made by the testing of data, whose results show that the relative error is approximately less than 10%, which can meet the engineering needs, and therefore, this proposed approach is valid and applicable in predicting mining induced surface subsidence. The model offers a novel method to predict surface subsidence in mining. |
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| Keywords: | mining induced surface subsidence genetic programming parameters |
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