Title :
Estimating mechanics parameters of rock mass based on improved genetic algorithm
Author :
Ling, Xianzhang ; Zhang, Feng ; Zhu, Zhanyuan ; Tang, Liang
Author_Institution :
Sch. of Civil Eng., Harbin Inst. of Technol., Harbin
Abstract :
To estimate the mechanics parameters of rock mass, the genetic algorithm (GA) is adopted Considering the weakness of GA on convergence performance, a new improved genetic algorithm (IGA) is developed based on the niche algorithm, adaptive probability of crossover and mutation, and elitism strategy. Optimum result of the Shubert function using the proposed algorithm shows that the global convergence performance of genetic algorithms is greatly improved. Based on these improved methods, the process of estimating mechanics parameters is established through the improved genetic algorithms, the finite element method and the theory of displacement back analysis, to estimate the mechanics parameters of rock mass. Moreover, the optimization displacement back analysis program (ODBA) is worked out. Finally, using this program, the mechanics parameters of rock mass in shisanling pumped storage station are estimated, and the results indicate that estimated parameters are compared well with field test mechanics parameters. Consequently, the new IGA should be popularized to estimate the mechanics parameters in geotechnical engineering.
Keywords :
finite element analysis; genetic algorithms; parameter estimation; rocks; Shisanling pumped storage station; Shubert function; adaptive crossover probability; adaptive mutation probability; displacement back analysis; elitism strategy; finite element method; genetic algorithm; geotechnical engineering; mechanics parameter estimation; niche algorithm; optimization displacement back analysis program; rock mass; Displacement control; Genetic algorithms; Parameter estimation; Testing; Adaptive Algorithms; Estimating parameters; Niche Algorithms; Optimization Displacement Back Analysis; the Improved Genetic Algorithms;
Conference_Titel :
Control and Decision Conference, 2008. CCDC 2008. Chinese
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-1733-9
Electronic_ISBN :
978-1-4244-1734-6
DOI :
10.1109/CCDC.2008.4598203