基于常规模拟退火算法的零偏VSP全波形反演面临着计算量大和耗时长的问题。为此提出了一种不同阶段对应不同扰动模型和退火方式的分段快速模拟退火(segmented fast simulated annealing,SFSA)反演策略,以提高零偏VSP资料全波形反演的效...基于常规模拟退火算法的零偏VSP全波形反演面临着计算量大和耗时长的问题。为此提出了一种不同阶段对应不同扰动模型和退火方式的分段快速模拟退火(segmented fast simulated annealing,SFSA)反演策略,以提高零偏VSP资料全波形反演的效率。在反演前期采用大模型扰动空间和较慢温度衰减速度,充分发挥全局搜索能力,而在后期引入限制因子产生扰动模型,在迭代不断增加的时候逐渐减小模型的扰动空间,同时采用较快的温度衰减速度,有效提高反演的速度,使反演快速收敛到最优解。基于相同的初始温度和马尔可夫链长度,分别利用基于SFSA和非常快速模拟退火(very fast simulated annealing,VFSA)方法进行零偏VSP纵波速度全波形反演测试。结果表明,基于SFSA的反演方法的反演效率提高约50%,在迭代次数更少的条件下能获得更好的反演效果。基于SFSA的零偏VSP全波形反演具有高效和高精度的特点,其反演结果为地震地质层位标定、成果解释及油气预测奠定了基础。展开更多
The purpose of this study is to examine optical spatial frequency spectroscopy analysis(SFSA)combined with visible resonance Raman(VRR)spectroscopic method,for thefirst time,to discriminate human brain metastases of l...The purpose of this study is to examine optical spatial frequency spectroscopy analysis(SFSA)combined with visible resonance Raman(VRR)spectroscopic method,for thefirst time,to discriminate human brain metastases of lung cancers adenocarcinoma(ADC)and squamous cell carcinoma(SCC)from normal tissues.A total of 31 label-free micrographic images of three type of brain tissues were obtained using a confocal micro-Raman spectroscopic system.VRR spectra of the corresponding samples were synchronously collected using excitation wavelength of 532 nm from the same sites of the tissues.Using SFSA method,the difference in the randomness of spatial frequency structures in the micrograph images was analyzed using Gaussian functionfitting.The standard deviations,calculated from the spatial frequencies of the micrograph images were then analyzed using support vector machine(SVM)classifier.The key VRR biomolecularfingerprints of carotenoids,tryptophan,amide II,lipids and proteins(methylene/methyl groups)were also analyzed using SVM classifier.All three types of brain tissues were identified with high accuracy in the two approaches with high correlation.The results show that SFSA–VRR can potentially be a dual-modal method to provide new criteria for identifying the three types of human brain tissues,which are on-site,real-time and label-free and may improve the accuracy of brain biopsy.展开更多
文摘基于常规模拟退火算法的零偏VSP全波形反演面临着计算量大和耗时长的问题。为此提出了一种不同阶段对应不同扰动模型和退火方式的分段快速模拟退火(segmented fast simulated annealing,SFSA)反演策略,以提高零偏VSP资料全波形反演的效率。在反演前期采用大模型扰动空间和较慢温度衰减速度,充分发挥全局搜索能力,而在后期引入限制因子产生扰动模型,在迭代不断增加的时候逐渐减小模型的扰动空间,同时采用较快的温度衰减速度,有效提高反演的速度,使反演快速收敛到最优解。基于相同的初始温度和马尔可夫链长度,分别利用基于SFSA和非常快速模拟退火(very fast simulated annealing,VFSA)方法进行零偏VSP纵波速度全波形反演测试。结果表明,基于SFSA的反演方法的反演效率提高约50%,在迭代次数更少的条件下能获得更好的反演效果。基于SFSA的零偏VSP全波形反演具有高效和高精度的特点,其反演结果为地震地质层位标定、成果解释及油气预测奠定了基础。
基金This research is supported by The Air Force Medical Center,China and in part of The Institute for Ultrafast Spectroscopy and Lasers(IUSL),the City College of the City University of New York.The authors would like to thank Mr.C.Y.Zhang,Mr.M.Z.Fan and Dr.X.H.Ni for their assistance in the experiments and suggestions concerning this paper.
文摘The purpose of this study is to examine optical spatial frequency spectroscopy analysis(SFSA)combined with visible resonance Raman(VRR)spectroscopic method,for thefirst time,to discriminate human brain metastases of lung cancers adenocarcinoma(ADC)and squamous cell carcinoma(SCC)from normal tissues.A total of 31 label-free micrographic images of three type of brain tissues were obtained using a confocal micro-Raman spectroscopic system.VRR spectra of the corresponding samples were synchronously collected using excitation wavelength of 532 nm from the same sites of the tissues.Using SFSA method,the difference in the randomness of spatial frequency structures in the micrograph images was analyzed using Gaussian functionfitting.The standard deviations,calculated from the spatial frequencies of the micrograph images were then analyzed using support vector machine(SVM)classifier.The key VRR biomolecularfingerprints of carotenoids,tryptophan,amide II,lipids and proteins(methylene/methyl groups)were also analyzed using SVM classifier.All three types of brain tissues were identified with high accuracy in the two approaches with high correlation.The results show that SFSA–VRR can potentially be a dual-modal method to provide new criteria for identifying the three types of human brain tissues,which are on-site,real-time and label-free and may improve the accuracy of brain biopsy.
