CAJ | 학술논문

为解决传统方法在概率积分法参数反演中存在的反演过程发散问题.将粒子群优化(PSO)算法纳入到文化算法(CA)框架中,提出了概率积分法参数反演的文化-随机粒子群优化(CA-rPSO)算法.以随机粒子群优化(rPSO)算法作为信念空间的进化算法,并将 PSO 作为群体空间的进化算法,形成两者独立并行进化的“双演化双促进”机制,按照误差平方和最小化准则构建适应度函数,反演出概率积分法参数.研究结果表明:对于常规布设形式的地表移动观测站,基于 CA-rPSO 反演概率积分法参数的收敛成功率为1.该结论具有较高的实用价值,且对矿山其它复杂参数寻优问题有着一定的指导意义.
위해결전통방법재개솔적분법삼수반연중존재적반연과정발산문제.장입자군우화(PSO)산법납입도문화산법(CA)광가중,제출료개솔적분법삼수반연적문화-수궤입자군우화(CA-rPSO)산법.이수궤입자군우화(rPSO)산법작위신념공간적진화산법,병장 PSO 작위군체공간적진화산법,형성량자독립병행진화적“쌍연화쌍촉진”궤제,안조오차평방화최소화준칙구건괄응도함수,반연출개솔적분법삼수.연구결과표명:대우상규포설형식적지표이동관측참,기우 CA-rPSO 반연개솔적분법삼수적수렴성공솔위1.해결론구유교고적실용개치,차대광산기타복잡삼수심우문제유착일정적지도의의.
@@@@To solve the divergence problem of parameters inversion in probability-integral method, a novel algorithm called random PSO embedded cultural framework (CA-rPSO) is proposed in this study through integrating PSO into the framework of cultural algorithm (CA). In CA-rPSO, the evolving algorithms of belief space and population space are represented with random PSO and PSO respectively, forming independent and parallel “dual evolution-dual promotion” mechanism. Subsequently, selecting the least sum square of errors as inversion criterion, the fitness function is then established so as to inverse the parameters of probability-integral method. The case study results show that in a traditional surface movement observation station, the parameters inversions of probability-integral method based on CA-rPSO acheive a convergence rate of 1, which indicates that the algorithm has a high practicability. The study is of significance for other complex mining problems with parameters optimization.