Cartan型模李超代数W(n)的伴随模

Cartan型模李超代数的分类是解决素特征域上单李超代数分类问题的关键。识别定理为素特征域上李代数分类问题的解决奠定了基础。仿照识别定理中对于Cartan型模李代数伴随模的理论,研究了Cartan型模李超代数W(n)的伴随模。通过对W(n)的Z_(2)-阶化分支的直和分解,得到了两类伴随模,进而给出了这两类伴随模之间的关系,并证明了它们的不可约性。

关于半对偶模的两个特殊模类及投射维数

利用同调代数的方法,讨论关于半对偶模W的余自反模类Cor W(R)和伴随余自反模类Acor W(R)的若干性质,其中Cor W(R)表示所有自然同态v N:W R Hom R(W,N)→N为同构的模N组成的类,Acor W(R)表示所有自然同态u M:M→Hom R(W,W R M)为同构的模M组成的类.研究模U的Cor W(R)-覆盖与模Hom R(W,U)的Acor W(R)-覆盖之间的关系,以及模U的Acor W(R)-包络与模W R U的Cor W(R)-包络之间的关系.进而证明了在特定条件下,Hom R(W,U)的Acor W(R)-投射维数小于等于U的Cor W(R)-投射维数,并且W R U的Cor W(R)-投射维数小于等于U的Acor W(R)-投射维数.

Adjoint Assimilation in Marine Ecosystem Models and an Example of Application

This paper aims at a review of the work carried out to date on the adjoint assimilation of data in marine ecosys-tem models since 1995. The structure and feature of the adjoint assimilation in marine ecosystem models are also introduced. To illustrate the application of the adjoint technique and its merits, a 4-variable ecosystem model coupled with a 3-D physical model is established for the Bohai Sea and the Yellow Sea. The chlorophyll concentration data derived from the SeaWiFS o-cean colour data are assimilated in the model with the technique. Some results are briefly presented.

The Nonlinear Interaction Process in the Wave Assimilation Model and Its Experiments

This paper presents a composite interaction formula based on the discrete-interaction operator of wave-wave nonlinear interaction for deriving its adjoint source function in the wave assimilation model. Assimilation experiments were performed using the significant wave heights observed by the TOPES/POSEIDON satellite, and the gradient distribution in the physical space was also analyzed preliminarily.

Rudiment of weak Doi-Hopf π-modules

The notion of weak Doi-Hopfπ-datum and weak Doi-Hopfπ-module are given as generalizations of an ordinary weak Doi-Hopf datum and weak Doi-Hopf module introduced in （Boehm, 2000）, also as a generalization of a Doi-Hopfπ-module introduced in （Wang, 2004）. Then we also show that the functor forgetting action or coaction has an adjoint. Furthermore we explain how the notion of weak Doi-Hopfπ-datum is related to weak smash product. This paper presents our preliminary results on weak Doi-Hopf group modules.

区间值模糊推理的全蕴涵方法

讨论了区间值上的三角模及伴随,获得了几个重要的结果。提出了IFMP和IFMT问题的区间值模糊推理的三I约束原则、反向三I原则、反向α-三I原则和反向三I约束原则。针对区间值上一般的三角模及其伴随,给出了IFMP、IFMT问题的区间值模糊推理的三I约束算法、反向三I算法、反向α-三I算法及反向三I约束算法解的计算公式,讨论了IFMP、IFMT问题的区间值模糊推理的反向三I算法的还原性。

A SVD-based ensemble projection algorithm for calculating the conditional nonlinear optimal perturbation

Conditional nonlinear optimal perturbation(CNOP) is an extension of the linear singular vector technique in the nonlinear regime.It represents the initial perturbation that is subjected to a given physical constraint,and results in the largest nonlinear evolution at the prediction time.CNOP-type errors play an important role in the predictability of weather and climate.Generally,when calculating CNOP in a complicated numerical model,we need the gradient of the objective function with respect to the initial perturbations to provide the descent direction for searching the phase space.The adjoint technique is widely used to calculate the gradient of the objective function.However,it is difficult and cumbersome to construct the adjoint model of a complicated numerical model,which imposes a limitation on the application of CNOP.Based on previous research,this study proposes a new ensemble projection algorithm based on singular vector decomposition(SVD).The new algorithm avoids the localization procedure of previous ensemble projection algorithms,and overcomes the uncertainty caused by choosing the localization radius empirically.The new algorithm is applied to calculate the CNOP in an intermediate forecasting model.The results show that the CNOP obtained by the new ensemble-based algorithm can effectively approximate that calculated by the adjoint algorithm,and retains the general spatial characteristics of the latter.Hence,the new SVD-based ensemble projection algorithm proposed in this study is an effective method of approximating the CNOP.

Numeric modelling and risk assessment of pollutions in the Chinese Bohai Sea

To simulate the dynamic process of total nitrogen(TN) in seas, numerical modelling combined with the adjoint method is implemented in this study. Because nonpoint source terms(ST) and initial values(IV) of TN are essential but difficult to determine, the adjoint method was applied to a numerical model, and the ST and IV terms of TN were inverted via routine monitoring data in the Bohai Sea. In twin experiments, the adjoint method was capable of inverting the prescribed spatio-temporally distributed ST and the spatial distributed IV. In practical experiments, the results demonstrated that the simulation precision with ST inversion was higher than that with IV inversion and was accurate with joint initial values and source term(IST) inversion. This result indicates that nonpoint source TN is essential for the simulation of TN concentration. Furthermore, the simulated results indicate that the pollution in three bays of the Bohai Sea is rather severe. The model in this study is not specific to the Bohai Sea and can be generalized to other areas, such as the Beibu Gulf. These findings may assist in the development of cost-effective controls for accidental or planned industrial pollutant releases into coastal waters.

Adjoint Method for an Inverse Problem of CCPF Model

The problem for determining the exchange rate function of 2D CCPF model by measurements on the partial boundary is considered and solved as one PDE-constraint optimization problem. The optimal variant is the minimum of a cost functional that quantifies the difference between the measurements and the exact solutions. Gradientbased algorithm is used to solve this optimization problem. At each step, the derivative of the cost functional with respect to the exchange rate function is calculated and only one forward solution and one adjoint solution are needed. One method based on the adjoint equation is developed and implemented. Numerical examples show the efficiency of the adjoint method.

Adjoint-free calculation method for conditional nonlinear optimal perturbations

Adjoint-free calculation method is proposed to compute conditional nonlinear optimal perturbations(CNOP) combined with initial perturbations and model parameter perturbations. The new approach avoids the use of adjoint technique in the optimization process. CNOPs respectively generated by ensemble-based and adjoint-based methods are compared based on a simple theoretical model.