Full-Text Search:
Home|About CNKI|User Service|中文
Add to Favorite Get Latest Update

Quantum genetic algorithm and its application in magnetotelluric data inversion

LUO Hong-Ming1,WANG Jia-Ying2,ZHU Pei-Min2,SHI Xue-Ming2,HE Guang-Ming1,CHEN Ai-Ping1,WEI Ming11 Sichuan Petroleum Geophysical Prospecting Company of CNPC Chuanqing Oilfield Service Co.Ltd, Chengdu 610213,China2 Institute of Geophysics and Geomatics,China University of Geosciences,Wuhan 430074,China  
Based on quantum mechanics,the quantum genetic algorithm(QGA)encodes with qubit instead of binary codes of classical genetic algorithms and makes directional updating with quantum rotation gates to replace the procedures of selection,crossover and mutation in genetic algorithms,therefore the algorithm possesses the great capabilities of internal parallel computing and quantum tunneling effect,to speed up the searching speed and improve the convergence rate greatly in searching the global optimization.In this paper,the author proposes a realizing scheme for geophysical inversion problem with nonlinear and multi-minimum properties,and test many synthetic models and real data to study the reliability in MT inversion.The computing efficiency of quantum genetic algorithm shows that it is a more stable and effective nonlinear inversion method with global convergence than traditional genetic algorithm.
Download(CAJ format) Download(PDF format)
CAJViewer7.0 supports all the CNKI file formats; AdobeReader only supports the PDF format.
©CNKI All Rights Reserved