Title :
Prediction Model of Chaos Neural Network for Surrounding Rock Pressure in Excavation of Tunnel with Small-interval
Author_Institution :
Sichuan Coll. of Archit. Technol., Deyang, China
Abstract :
Surrounding rock pressure of tunnel is the key factor to analyze the stability of surrounding rock. However, the deformation of surrounding rock is affected by many factors among which there are intense non-linear relation, so it is difficult to predict it effectively. In this paper, the method based on chaos neural network model is put forward, the feasibility of prediction techniques of combination of chaos and neural network is analyzed and surrounding rock pressure changing with time is simulated and calculated. From a new perspective, prediction issue of surrounding rock pressure is explorative researched. The establishment and prediction method for this theory are systematically discussed, which provides an effective technical method for the research on this theory. The result shows that the method is with high-precision prediction, which can meet the requirements of project and control.
Keywords :
geotechnical engineering; neural nets; prediction theory; rocks; structural engineering computing; tunnels; chaos neural network; deformation; nonlinear relation; prediction model; stability; surrounding rock pressure; tunnel excavation; Artificial neural networks; Chaos; Deformable models; Neurons; Predictive models; Pressure measurement; Time measurement; BP Neural Model; Chaos Optimization; Surrounding Rock; Tunnel;
Conference_Titel :
Artificial Intelligence and Computational Intelligence (AICI), 2010 International Conference on
Conference_Location :
Sanya
Print_ISBN :
978-1-4244-8432-4
DOI :
10.1109/AICI.2010.73