Abstract：Rockburst is a complicated dynamic destabilization failure of rock. Because there are many factors affecting the occurrence of rockburst, so it is difficult to predict the possibility and intensity of occurrence. This article is based on artificial intelligence expert system method, in view of the fuzziness and randomness characteristics of the evaluation process, a fuzzy comprehensive prediction model of rockburst intensity classification is established. Through the knowledge acquisition of rockburst intensity classification prediction, firstly, rock brittleness coefficient σc/σt, rock stress coefficient σθ/σc, initial stress level σ1/σc, elastic energy index Wet and rock fragility index Is are selected as rockburst evaluation indexes, using the fuzzy mathematics method to determine the membership function and the weight of each index| Then the acquired knowledge is expressed in the form of rule programming, and the knowledge base of rockburst intensity classification prediction expert system is established, And the corresponding analysis and calculation program is compiled| Finally, the proposed method is verified by some examples of rockburst engineering, the predicted results are consistent with the actual situation, which provides a new effective way for the prediction of rockburst.
詹金武 李涛 谭忠盛 李超. 基于人工智能专家系统的岩爆烈度分级预测研究[J]. 土木工程学报, 2017, 50(S1): 99-104.
Zhan Jinwu Li Tao Tan Zhongsheng Li Chao. Study on prediction of rockburst intensity classification with artificial intelligence expert system. 土木工程学报, 2017, 50(S1): 99-104.
