Application of Hybrid Genetic Algorithm in Ground Stress Inversion

Ran Gang Yu; Yong Tian

doi:10.4028/www.scientific.net/AMM.90-93.337

Paper Titles

Research about Different Molding Methods’ Effect on the Resistance against Frost and Shrinkage of Cement Stabilized Gravel
p.317

Soil Parameter Identification Based on Field Monitoring Value of Displacement and Stress in Pit Retaining Structure
p.323

Study on Landslide Early Warning of Mayanpo Slope at Xiangjiaba Hydropower Station
p.328

Model Test of Socketed Depth’s Influence on Bearing Mechanism in Rock-Socketed Pile
p.332

Application of Hybrid Genetic Algorithm in Ground Stress Inversion
p.337

Stability Evaluation on High Rock Slope of Open-Pit for Ash Storage
p.342

An Experimental Study on Basic Engineering Properties of Paper Sludge Ash (PS Ash)
p.347

Analysis on Types of In Situ Stress Field and its Effect to Roadway in Deep Coal Mines
p.353

Numerical Analyses for Layered Foundation by Coupling Finite and Axis-Radiate Infinite Elements
p.359

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 90-93Application of Hybrid Genetic Algorithm in Ground...

Application of Hybrid Genetic Algorithm in Ground Stress Inversion

Abstract:

This paper propose genetic algorithm combined with neural networks, greatly improving the convergence rate of neural network aim at the disadvantage of the traditional BP neural network inversion method is easy to fall into local minimum and slow convergence.Finally, verified the feasibility and superiority of the above methods through the successful initial ground stress inversion of actual project.