A Study of Adaptive Quantum Genetic Inversion Algorithm and Its Application to Magnetotelluric Data Inversion

摘要：

Quantum Genetic Algorithm (QGA) has been introduced to the nonlinear inversion of magnetotelluric data. Premature convergence has been observed in numerical tests using conventional QGA. Thus we runs QGA with a series of adaptive model spaces, which, according to the verification using some test functions and synthetic magnetotelluric data inversion, can effectively suppress premature phenomenon. The Adaptive Quantum Genetic Algorithm (AQGA) dynamically adjusts the model search space of QGA so that it can adaptively search the optimization model in the iteration process and in turn has a higher efficiency and results in a better solution.

关键词： Adaptive Quantum Genetic Algorithm (QGA) Magnetotelluric (MT) Inversion Nonlinear

作者: Jianke Fan Xueming Shi Hongming Luo Min Xiao Guoshi Yang Xuhui Zhang

作者单位: key laboratory of exploration technologies for oil and gas resources (Yangtze University), Ministry the Institute of Geophysics and Geomatics, China University of Geosciences, Wuhan, 430074, China

会议类型: 国际会议

会议名称: The Second International Symposium on Intelligence Computation and Applications(ISICA 2007)(第二届智能计算及其应用国际会议)

会议地点: 武汉

会议语种:英文

在线出版日期: 2007-09-21（万方平台首次上网日期，不代表论文的发表时间）