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| ARTIFICIAL NEURAL NETWORK PREDICTION MODEL OF MINING-INDUCED DAMAGE OF BUILDINGS |
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Abstract The main factors affecting the mining-induced damage degree of buildings are comprehensively analyzed. Then the model is established to predict the damage degree of buildings by applying the theory of artificial neural network(ANN). Based on a large amount of cases related to buildings damaged by mining，the predicted results of the model and the measured values are compared and analyzed. The results show that it is feasible to predict the mining-induced damage degree of buildings by ANN technology.
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Received: 01 April 2002
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CHEN Weizhong1*, LIU Xinyu1, 2, YANG Jianping1, WANG Wei1, 2, ZANG Zhonghai3, DING Hongyuan3, ZHANG Zheyuan3, WANG Xiaogang3, SHI Zhengrong1. Development of a large-scale 3D physical model test system for underground energy storage caverns and its model experimental study[J]. , 2026, 45(6): 1615-1628. |
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