CAJ | 학술논문

地震反演问题常常需要一些非线性全局最优化的方法。近年来，基于生物学、物理学、人工智能和一些非线性科学而发展了一些具有全局优化性能且通用性强的随机搜索算法，如：遗传算法、模拟退火、禁忌搜索和混沌搜索等。作者主要针对地震勘探反演问题的应用综述了这四种非线性随机优化方法的原理和特点，并对它们的性能作了一定的分析和比较。
지진반연문제상상수요일사비선성전국최우화적방법。근년래，기우생물학、물이학、인공지능화일사비선성과학이발전료일사구유전국우화성능차통용성강적수궤수색산법，여：유전산법、모의퇴화、금기수색화혼돈수색등。작자주요침대지진감탐반연문제적응용종술료저사충비선성수궤우화방법적원리화특점，병대타문적성능작료일정적분석화비교。
Seismic inversion problems must be solved by non-linear global optimization methods. In recent years, some non-linear stochastic optimistic algorithms are developed by biology, physics, artificial intelligence and nonlinear science, such as Genetic algorithm, Simulated annealing, Tabu searching and Chaos searching et al. In this paper, the principles and characteristics of four stochastic optimistic algorithms are summarized, and their performances are analyzed and compared on the applications of seismic inversion problems.