CAJ | 학술논문

针对微震源精确定位问题,提出了一种结合遗传粒子群算法( genetic algorithm and particle swarm optimization,GAPSO)和拟牛顿BFGS修正公式的联合精确微震源定位的方法。新的联合算法引入了交叉变异功能,能有效避免PSO易收敛于局部极值的缺点,然后将其初步定位结果作为初始值带入BFGS算法,有效改善了BFGS定位精度依赖于初始值选取的缺点。实地实验结果表名：此方法相较于PSO及经典定位算法,在x,y,z三个方向上的精度都得到了提高。
침대미진원정학정위문제,제출료일충결합유전입자군산법( genetic algorithm and particle swarm optimization,GAPSO)화의우돈BFGS수정공식적연합정학미진원정위적방법。신적연합산법인입료교차변이공능,능유효피면PSO역수렴우국부겁치적결점,연후장기초보정위결과작위초시치대입BFGS산법,유효개선료BFGS정위정도의뢰우초시치선취적결점。실지실험결과표명：차방법상교우PSO급경전정위산법,재x,y,z삼개방향상적정도도득도료제고。
Be aimed at the problem of locating Microseism source, proposing a Combined positioning method which combine Genetic Particle Swarm Optimization with Quasi-newton BFGS corrections method. The new com-bined algorithm add the function of crossover and mutation that can effectively avoid PSO’ S weakness of falling into the local extremum,then use the GAPSO’ s result as the initial value of BFGS, in this way, positioning accuracy can be improved. The field experiment results proved that to compare with the PSO and classical Location Algo-rithm, the location pricision has been significantly improved.