• 其他 •

粒子群投影寻踪算法在岩爆预测中的应用

1. （1.北京理工大学 爆炸科学与技术国家重点实验室,北京 100081； 2.华北科技学院 建筑学院,北京 101601）
• 收稿日期:2012-05-15 出版日期:2012-12-29 发布日期:2012-12-29
• 基金资助:

爆炸科学与技术国家重点实验室基金资助项目(ZDKT0826,YBKT091)

Application of Projection Pursuit Model and Particle Swarm Optimization in Rock Burst Prediction

ZHOU  Xuan-Chi-1, BAI  Chun-Hua-1, WANG  Zhong-Qi-1, LIN  Da-Chao-2

1. (1. State Key Laboratory of Explosion Science and Technology, Beijing Institute of Technology, Beijing 100081, China; 2. Department of Civil Engineering, North China Institute of Science and Technology, Beijing 101601, China)
• Received:2012-05-15 Online:2012-12-29 Published:2012-12-29

Abstract: In order to construct the measure of rock burst intensity, the ratio of maximum tangential stress of cave chamber to uniaxial compressive strength of rock, brittleness coefficient and elastic energy index are chosen as the discriminant index, an appropriate analysis model for rock burst prediction was established based on particle swarm optimization and projection pursuit algorithm. Firstly, for the sake of ensuring the accuracy of the model parameters, particle swarm optimization is used to optimize the projection index function, meanwhile the non-linear relationship between projected value and empirical value is obtained by use of logistic curve function. The study shows that the prediction of rock burst intensity with use of the regression model based on particle swarm and projection pursuit has the advantage over traditional forecasting methods in that the deviation caused by subjective reasons can be avoided and its prediction precision is high. Finally, the model was applied to the rock burst prediction of Qinling tunnel and Dongguashan copper ore and the result corresponds with actual situation which shows scientificity, feasibility and effectiveness of the model in rock burst prediction.