【作者】 赵同彬；

【导师】 谭云亮；

【作者基本信息】 山东科技大学 ， 安全技术及工程， 2004， 硕士

【摘要】 最优化方法是进行巷道位移反分析的有力工具，如果优化迭代方法选择不当，将导致迭代过程收敛缓慢、解的稳定性差、陷入局部极小值等问题，不能保证搜索到全局最优解。而近些年来发展起来的遗传算法在最优化方面具有许多优良特性，本文将遗传算法应用到巷道位移反分析的研究中。论文根据遗传算法的原理成功地求解了多峰函数和多变量函数的极值问题，还对影响优化结果的遗传算法运行参数作了初步讨论。提出了用影响度和灵敏度两个指标作为巷道位移反分析可反演性的评价标准，针对待反演的弹性模量E、泊松比μ、内聚力C和内摩擦角φ以及初始地应力σ_x、σ_y、τ_xy的可反演性进行了具体而详细的研究。采用遗传算法与FLAC数值软件相结合的方法，开发了基于遗传算法的巷道位移反分析程序，用具体的弹塑性巷道位移算例对该方法进行了验证。结果表明，用遗传算法进行巷道位移反分析的方法是一种值得推广的新方法。更多还原

【Abstract】 The optimization method is an effective tool in back-analysis of displacements of roadway, choosing the bad iteration method will lead to many problems, such as slow constringent speed, bad stability of solutions, local minimization. The globally optimal solution can’t be found out. However, the developing genetic algorithm method in recent years has many good characteristics in optimization, this paper will apply the genetic algorithm method to the research on back-analysis of displacements of roadway. It has successfully solved the extreme problems of multimodal function and multi-variable function on the ground of genetic algorithm theory. A preliminary discussion about running parameters of genetic algorithm which will affect the optimization results was made. This paper puts forward the influence degree index and sensitivity index as the evaluation standards of back-analysis feasibility, studies the feasibility of back-analysis about elastic modulus, poisson rate, cohesion, internal friction angle and initial ground pressure(x, y, xy) in detail. With the combination of genetic algorithm and FLAC numerical software, it also develops the back-analysis of displacement program on the basis of genetic algorithm method, and tests this method with specific elastic-plastic displacement example. The results indicate that the back-analysis of displacements with use of genetic algorithm is a good method worth being popularized更多还原