Classical multi-channel technology can significantly reduce the pre-stack seismic inversion uncertainty, especially for complex geology such as high dipping structures. However, due to the consideration of complex str...Classical multi-channel technology can significantly reduce the pre-stack seismic inversion uncertainty, especially for complex geology such as high dipping structures. However, due to the consideration of complex structure or reflection features, the existing multi-channel inversion methods have to adopt the highly time-consuming strategy of arranging seismic data trace-by-trace, limiting its wide application in pre-stack inversion. A fast pre-stack multi-channel inversion constrained by seismic reflection features has been proposed to address this issue. The key to our method is to re-characterize the reflection features to directly constrain the pre-stack inversion through a Hadamard product operator without rearranging the seismic data. The seismic reflection features can reflect the distribution of the stratum reflection interface, and we obtained them from the post-stack profile by searching the shortest local Euclidean distance between adjacent seismic traces. Instead of directly constructing a large-size reflection features constraint operator advocated by the conventional methods, through decomposing the reflection features along the vertical and horizontal direction at a particular sampling point, we have constructed a computationally well-behaved constraint operator represented by the vertical and horizontal partial derivatives. Based on the Alternating Direction Method of Multipliers (ADMM) optimization, we have derived a fast algorithm for solving the objective function, including Hadamard product operators. Compared with the conventional reflection features constrained inversion, the proposed method is more efficient and accurate, proved on the Overthrust model and a field data set.展开更多
The properties of the same pigments in murals are affected by different concentrations and particle diameters,which cause the shape of the spectral reflectance data curve to vary,thus influencing the outcome of matchi...The properties of the same pigments in murals are affected by different concentrations and particle diameters,which cause the shape of the spectral reflectance data curve to vary,thus influencing the outcome of matching calculations.This paper proposes a spectral matching classification method of multi-state similar pigments based on feature differences.Fast principal component analysis(FPCA)was used to calculate the eigenvalue variance of pigment spectral reflectance,then applied to the original reflectance values for parameter characterization.We first projected the original spectral reflectance from the spectral space to the characteristic variance space to identify the spectral curve.Secondly,the relative distance between the eigenvalues in the eigen variance space is combined with the JS(Jensen-Shannon)divergence to express the difference between the two spectral distributions.The JS information divergence calculates the relative distance between the eigenvalues.Experimental results showthat our classification method can be used to identify the spectral curves of the same pigment under different states.The value of the root means square error(RMSE)decreased by 12.0817,while the mean values of the mean absolute percentage error(MAPE)and R2 increased by 0.0965 and 0.2849,respectively.Compared with the traditional spectral matching algorithm,the recognition error was effectively reduced.展开更多
Ganoderma lucidum(G. lucidum) spores as a valuable Chinese herbal medicine have vast marketable prospect for its bioactivities and medicinal efficacy. This study aims at the development of an effective and simple anal...Ganoderma lucidum(G. lucidum) spores as a valuable Chinese herbal medicine have vast marketable prospect for its bioactivities and medicinal efficacy. This study aims at the development of an effective and simple analytical method to distinguish G. lucidum spores from its fruiting body, which is of essential importance for the quality control and fast discrimination of raw materials of Chinese herbal medicine. Attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy combined with the appropriate chemometric methods including penalized discriminant analysis, principal component discriminant analysis and partial least squares discriminant analysis has been proven to be a rapid and powerful tool for discrimination of G. lucidum spores and its fruiting body with classification accuracy of 99%. The model leads to a well-performed selection of informative spectral absorption bands which improve the classification accuracy, reduce the model complexity and enhance the quantitative interpretations of the chemical constituents of G. lucidum spores regarding its anticancer effects.展开更多
基金We would like to acknowledge the sponsorship of the National Natural Science Foundation of China(42004092,42030103,41974119)Marine S&T Fund of Shandong Province for Pilot National Laboratory for Marine Science and Technology(Qingdao)(Grant No.2021QNLM020001-6)Young Elite Scientists Sponsorship Program by CAST(2021QNRC001).
文摘Classical multi-channel technology can significantly reduce the pre-stack seismic inversion uncertainty, especially for complex geology such as high dipping structures. However, due to the consideration of complex structure or reflection features, the existing multi-channel inversion methods have to adopt the highly time-consuming strategy of arranging seismic data trace-by-trace, limiting its wide application in pre-stack inversion. A fast pre-stack multi-channel inversion constrained by seismic reflection features has been proposed to address this issue. The key to our method is to re-characterize the reflection features to directly constrain the pre-stack inversion through a Hadamard product operator without rearranging the seismic data. The seismic reflection features can reflect the distribution of the stratum reflection interface, and we obtained them from the post-stack profile by searching the shortest local Euclidean distance between adjacent seismic traces. Instead of directly constructing a large-size reflection features constraint operator advocated by the conventional methods, through decomposing the reflection features along the vertical and horizontal direction at a particular sampling point, we have constructed a computationally well-behaved constraint operator represented by the vertical and horizontal partial derivatives. Based on the Alternating Direction Method of Multipliers (ADMM) optimization, we have derived a fast algorithm for solving the objective function, including Hadamard product operators. Compared with the conventional reflection features constrained inversion, the proposed method is more efficient and accurate, proved on the Overthrust model and a field data set.
基金This work was supported in part by the National Science Foundation of China:Shaanxi Natural Science Basic Research Project(2021JM-377)Science and Technology Cooperation Project of Shaanxi Provincial Department of Science and Technology(2020KW-012)University Talent Service Enterprise Project of Xi’an Science and Technology Bureau(GXYD10.1)。
文摘The properties of the same pigments in murals are affected by different concentrations and particle diameters,which cause the shape of the spectral reflectance data curve to vary,thus influencing the outcome of matching calculations.This paper proposes a spectral matching classification method of multi-state similar pigments based on feature differences.Fast principal component analysis(FPCA)was used to calculate the eigenvalue variance of pigment spectral reflectance,then applied to the original reflectance values for parameter characterization.We first projected the original spectral reflectance from the spectral space to the characteristic variance space to identify the spectral curve.Secondly,the relative distance between the eigenvalues in the eigen variance space is combined with the JS(Jensen-Shannon)divergence to express the difference between the two spectral distributions.The JS information divergence calculates the relative distance between the eigenvalues.Experimental results showthat our classification method can be used to identify the spectral curves of the same pigment under different states.The value of the root means square error(RMSE)decreased by 12.0817,while the mean values of the mean absolute percentage error(MAPE)and R2 increased by 0.0965 and 0.2849,respectively.Compared with the traditional spectral matching algorithm,the recognition error was effectively reduced.
文摘Ganoderma lucidum(G. lucidum) spores as a valuable Chinese herbal medicine have vast marketable prospect for its bioactivities and medicinal efficacy. This study aims at the development of an effective and simple analytical method to distinguish G. lucidum spores from its fruiting body, which is of essential importance for the quality control and fast discrimination of raw materials of Chinese herbal medicine. Attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy combined with the appropriate chemometric methods including penalized discriminant analysis, principal component discriminant analysis and partial least squares discriminant analysis has been proven to be a rapid and powerful tool for discrimination of G. lucidum spores and its fruiting body with classification accuracy of 99%. The model leads to a well-performed selection of informative spectral absorption bands which improve the classification accuracy, reduce the model complexity and enhance the quantitative interpretations of the chemical constituents of G. lucidum spores regarding its anticancer effects.
