Algorithm Studies on How to Obtain a Conditional Nonlinear Optimal Perturbation (CNOP)

The conditional nonlinear optimal perturbation (CNOP), which is a nonlinear generalization of the linear singular vector (LSV), is applied in important problems of atmospheric and oceanic sciences, including ENSO predictability, targeted observations, and ensemble forecast. In this study, we investigate the computational cost of obtaining the CNOP by several methods. Differences and similarities, in terms of the computational error and cost in obtaining the CNOP, are compared among the sequential quadratic programming (SQP) algorithm, the limited memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) algorithm, and the spectral projected gradients (SPG2) algorithm. A theoretical grassland ecosystem model and the classical Lorenz model are used as examples. Numerical results demonstrate that the computational error is acceptable with all three algorithms. The computational cost to obtain the CNOP is reduced by using the SQP algorithm. The experimental results also reveal that the L-BFGS algorithm is the most effective algorithm among the three optimization algorithms for obtaining the CNOP. The numerical results suggest a new approach and algorithm for obtaining the CNOP for a large-scale optimization problem.

Changes in plant biomass and species composition of alpine Kobresia meadows along altitudinal gradient on the Qinghai-Tibetan Plateau

Alpine Kobresia meadows are major vegetation types on the Qinghai-Tibetan Plateau. There is growing concern over their relationships among biodiversity, productivity and environments. Despite the importance of species composition, species richness, the type of different growth forms, and plant biomass structure for Kobresia meadow ecosystems, few studies have been focused on the relationship between biomass and environmental gradient in the Kobresia meadow plant communities, particularly in relation to soil moisture and edaphic gradients. We measured the plant species composition, herbaceous litter, aboveground and belowground biomass in three Kobresia meadow plant communities in Haibei Alpine Meadow Ecosystem Research Station from 2001 to 2004. Community differences in plant species composition were reflected in biomass distribution. The total biomass showed a decrease from 13196.96 +/- 719.69 g/m(2) in the sedge-dominated K. tibetica swamp to 2869.58 +/- 147.52 g/m(2) in the forb and sedge dominated K. pygmaea meadow, and to 2153.08 +/- 141.95 g/m(2) in the forbs and grasses dominated K. humilis along with the increase of altitude. The vertical distribution of belowground biomass is distinct in the three meadow communities, and the belowground biomass at the depth of 0-10 cm in K. tibetica swamp meadow was significantly higher than that in K. humilis and K. pygmaea meadows (P < 0.01). The herbaceous litter in K. tibetica swamp was significantly higher than those in K. pygnaeca and K. humilis meadows. The effects of plant litter are enhanced when ground water and soil moisture levels are raised. The relative importance of litter and vegetation may vary with soil water availability. In the K. tibetica swamp, total biomass was negatively correlated to species richness (P < 0.05); aboveground biomass was positively correlated to soil organic matter, soil moisture, and plant cover (P < 0.05); belowground biomass was positively correlated with soil moisture (P < 0.05). However, in the K. pygnaeca and K. humilis meadow communities, aboveground biomass was positively correlated to soil organic matter and soil total nitrogen (P < 0.05). This suggests that the distribution of biomass coincided with soil moisture and edaphic gradient in alpine meadows.

强化学习算法中启发式回报函数的设计及其收敛性分析

回报函数设计的好与坏对学习系统性能有着重要作用,按回报值在状态-动作空间中的分布情况,将回报函数的构建分为两种形式:密集函数和稀疏函数,分析了密集函数和稀疏函数的特点.提出启发式回报函数的基本设计思路,利用基于保守势函数差分形式的附加回报函数,给学习系统提供更多的启发式信息,并对算法的最优策略不变性和迭代收敛性进行了证明.启发式回报函数能够引导学习,加快学习进程,从而可以实现强化学习在实际大型复杂系统应用中的实时控制和调度.

青藏高原东部电性结构特征及其构造意义

Eastern Himalayan Syntaxis (EHS) and its surroundings (eastern margin of Tibet) is one of the most complicated tectonic areas in the world. As the exhaust opening of the balanced materials of the Tibetan Plateau during the collision of Indan and Eurasian plates, the deep structure beneath EHS surrounding region is referred to as the key to the study of the dynamics of the plateau. EHS3D project, sponsored by NSFC, has been proposed to explore the deep electric features of the area. During the first stage of EHS3D(2006-2008), MT+LMT measurements have been conducted along two lines from Chayu to Qingshuihe (EHS3D-3) and Chayu to Ruoergai (EHS3D-2). This paper will discuss the MT models of EHS3D-3 line. By the data procrssing, including distortion analysis, Robust estimation and strike decomposition, rotated apparent resitivities and phases have been obtained for each station. Then conventional 2-D inversion algorithms (NLCG and RRI) were employed to produce 2-D models. The final preferred 2-D model suggests that the upper crust consists of resistive blocks while in mid-lower crust there are two extensive conductive bodies beneath Lhasa block and Qiangtang terrain respectively. Jinshajiang suture is a gradient belt and Bangong-Nujiang suture appear a conductive belt dipping to the north. . We concluded that the formation of the two conductive bodies attributed to the partial melt and fluids in the lower crust. The regional electric strike derived from decomposition analysis indicates that the crust and upper mantle move in different manners. The upper crust moves like slips of rigid blocks along major slip faults while the lower crust creeps as a flow in the conductive channels.

青藏高原东部电性结构特征及地球动力学意义

As the largest and highest plateau on the Earth, the Tibetan Plateau has been a key location for understanding the processes of mountain building and plateau formation during India-Asia continent-continent collision. As the front-end of the collision, the geological structure of eastern Tibetan Plateau is very complex. It is ideal as a natural laboratory for investigating the formation and evolution of the Tibetan Plateau. Institute of Geophysics, Chinese Academy of Sciences (CAS) carried out MT survey from XiaZayii to Qingshuihe in the east part of the plateau in 1998. After error analysis and distortion analysis, the Non-linear Conjugate Gradient inversion(NLCG), Rapid Relaxation Inversin (RRI) and 2D OCCAM Inversion algorithms were used to invert the data. The three models obtained from 3 algorithms provided similar electrical structure and the NLCG model fit the observed data better than the other two models. According to the analysis of skin depth, the exploration depth of MT in Tibet is much more shallow than in stable continent. For example, the Schmucker depth at period 100s is less than 50km in Tibet, but more than 100km in Canadian Shield. There is a high conductivity layer at the depth of several kilometers beneath middle Qiangtang terrane, and almost 30 kilometers beneath northern Qiangtang terrane. The sensitivity analysis of the data predicates that the depth and resistivity of the crustal high conductivity layer are reliable. The MT results provide a high conductivity layer at 20~40km depth, where the seismic data show a low velocity zone. The experiments show that the rock will dehydrate and partially melt in the relative temperature and pressure. Fluids originated from dehydration and partial melting will seriously change rheological characteristics of rock. Therefore, This layer with low velocity and high conductivity layer in the crust is a weak layer. There is a low velocity path at the depth of 90-110 km beneath southeastern Tibetan Plateau and adjacent areas from seismology results. The analysis on the temperature and rheological property of the lithosphere show that the low velocity path is also weak. GPS measurements and the numerical simulation of the crust-mantle deformation show that the movement rate is different for different terranes. The regional strike derived from decomposition analysis for different frequency band and seismic anisotropy indicate that the crust and upper mantle move separately instead of as a whole. There are material flow in the eastern and southeastern Tibetan Plateau. Therefore, the faults, the crustal and upper mantle weak layers are three different boundaries for relatively movement. Those results support the "two layer wedge plates" geodynamic model on Tibetan formation and evolution.

基于信息重建技术的地震信号处理方法研究

The dissertation addressed the problems of signals reconstruction and data restoration in seismic data processing, which takes the representation methods of signal as the main clue, and take the seismic information reconstruction (signals separation and trace interpolation) as the core. On the natural bases signal representation, I present the ICA fundamentals, algorithms and its original applications to nature earth quake signals separation and survey seismic signals separation. On determinative bases signal representation, the paper proposed seismic dada reconstruction least square inversion regularization methods, sparseness constraints, pre-conditioned conjugate gradient methods, and their applications to seismic de-convolution, Radon transformation, et. al. The core contents are about de-alias uneven seismic data reconstruction algorithm and its application to seismic interpolation. Although the dissertation discussed two cases of signal representation, they can be integrated into one frame, because they both deal with the signals or information restoration, the former reconstructing original signals from mixed signals, the later reconstructing whole data from sparse or irregular data. The goal of them is same to provide pre-processing methods and post-processing method for seismic pre-stack depth migration. ICA can separate the original signals from mixed signals by them, or abstract the basic structure from analyzed data. I surveyed the fundamental, algorithms and applications of ICA. Compared with KL transformation, I proposed the independent components transformation concept (ICT). On basis of the ne-entropy measurement of independence, I implemented the FastICA and improved it by covariance matrix. By analyzing the characteristics of the seismic signals, I introduced ICA into seismic signal processing firstly in Geophysical community, and implemented the noise separation from seismic signal. Synthetic and real data examples show the usability of ICA to seismic signal processing and initial effects are achieved. The application of ICA to separation quake conversion wave from multiple in sedimentary area is made, which demonstrates good effects, so more reasonable interpretation of underground un-continuity is got. The results show the perspective of application of ICA to Geophysical signal processing. By virtue of the relationship between ICA and Blind Deconvolution , I surveyed the seismic blind deconvolution, and discussed the perspective of applying ICA to seismic blind deconvolution with two possible solutions. The relationship of PC A, ICA and wavelet transform is claimed. It is proved that reconstruction of wavelet prototype functions is Lie group representation. By the way, over-sampled wavelet transform is proposed to enhance the seismic data resolution, which is validated by numerical examples. The key of pre-stack depth migration is the regularization of pre-stack seismic data. As a main procedure, seismic interpolation and missing data reconstruction are necessary. Firstly, I review the seismic imaging methods in order to argue the critical effect of regularization. By review of the seismic interpolation algorithms, I acclaim that de-alias uneven data reconstruction is still a challenge. The fundamental of seismic reconstruction is discussed firstly. Then sparseness constraint on least square inversion and preconditioned conjugate gradient solver are studied and implemented. Choosing constraint item with Cauchy distribution, I programmed PCG algorithm and implement sparse seismic deconvolution, high resolution Radon Transformation by PCG, which is prepared for seismic data reconstruction. About seismic interpolation, dealias even data interpolation and uneven data reconstruction are very good respectively, however they can not be combined each other. In this paper, a novel Fourier transform based method and a algorithm have been proposed, which could reconstruct both uneven and alias seismic data. I formulated band-limited data reconstruction as minimum norm least squares inversion problem where an adaptive DFT-weighted norm regularization term is used. The inverse problem is solved by pre-conditional conjugate gradient method, which makes the solutions stable and convergent quickly. Based on the assumption that seismic data are consisted of finite linear events, from sampling theorem, alias events can be attenuated via LS weight predicted linearly from low frequency. Three application issues are discussed on even gap trace interpolation, uneven gap filling, high frequency trace reconstruction from low frequency data trace constrained by few high frequency traces. Both synthetic and real data numerical examples show the proposed method is valid, efficient and applicable. The research is valuable to seismic data regularization and cross well seismic. To meet 3D shot profile depth migration request for data, schemes must be taken to make the data even and fitting the velocity dataset. The methods of this paper are used to interpolate and extrapolate the shot gathers instead of simply embedding zero traces. So, the aperture of migration is enlarged and the migration effect is improved. The results show the effectiveness and the practicability.

Total analytical method for Radix astragali extract using two-binary multi-segment gradient elution liquid chromatography

There is an urgent need for thorough analysis of Radix astragali, a widely used Chinese herb, for quality control purposes. This paper describes the development of a total analytical method for Radix astragali extract, a multi-component complex mixture. Twenty-four components were separated step by step from the extract using a series of isocratic isopropanol-methanol elutions, and then 42 components were separated similarly using methanol-water elutions. Based on the log k(w) and -S of the 66 components obtained from the above procedure and the optimization software developed in our laboratory, an optimum elution program consisting of seven methanol-water segments and four isopropanol-methanol segments was developed to finish the task of analyzing the total components in a single run. Under optimized gradient conditions, the sample of Radix astragali extract was analyzed. As expected, most of the components were well separated and the experimental chromatogram was in a good agreement with the predicted one.

Spatial temperature gradient capillary electrophoresis for DNA mutation detection

A continuous spatial temperature gradient was established in capillary electrophoresis by using a simple temperature control device. The temperature profile along the capillary was predicted by theoretical calculations. A nearly linear spatial temperature gradient was established and applied to DNA mutation detection. By spanning a wide temperature range, it was possible to perform simultaneous heteroduplex analysis for various mutation types that have different melting temperatures.