需求变化下中国进口种类增长福利效应测算——基于替代弹性混合估计方法

基于1996—2019年CEPII-BACI数据库中国HS6位数进口产品数据,借鉴精确价格指数和替代弹性混合估计方法,测算了需求变化情形下中国进口种类增长福利效应。结果发现:忽略需求变化会严重低估中国进口种类增长福利效应。1996—2019年,需求变化情形下,混合估计方法测算的传统价格指数向上偏误32.755%,进口种类增长福利效应相当于GDP的5.229%,而标准估计方法低估进口种类增长福利效应达到GDP的2.623%。福利分解显示,HS6位数产品层面和ISIC2位数行业层面均呈现集中趋势;BEC分解表明中国“重生产和轻消费”的进口模式依然明显。研究完善了需求变化情形下进口种类增长福利效应估算理论,为中国实施扩大进口战略和构建新发展格局提供了重要的经验证据。

混合H_2/H_∞参数辨识

研究了混合H2/H∞参数辨识问题.将混合H2/H∞估计方法应用到系统参数辨识中,给出了混合H2/H∞参数辨识算法.所得的算法不仅能满足规定的鲁棒性能,且为最小二乘(LS)参数估计误差判据提供了一个最优上界.结果表明:提高辨识的鲁棒性,需要牺牲辨识的精度作为代价.最后,仿真结果也验证了该方法的有效性.

信息获取能力会影响果农的销售渠道选择吗?

进入数字经济时代后,信息逐步成为影响农户行为决策的关键因素。本研究基于行为转变理论和计划行为理论,利用来自中国黄土高原优势产区1074户微观数据,通过运用Ordered Probit模型,实证检验信息获取能力对果农销售渠道选择的影响,并进一步运用条件混合过程估计法(CMP方法)对模型进行了内生性检验。研究结果表明:(1)当前,传统销售渠道的中间商(果贩)仍然是果农销售农产品的主要方式;(2)信息获取能力对果农销售渠道的选择有显著正向影响,即信息工具使用水平对果农进入市场壁垒更高的销售渠道具有促进作用;(3)信息获取能力正向显著影响新、中生代苹果户群体对销售渠道的选择。因此,政府应在完善农村信息基础设施和信息服务体系的同时,优化升级农产品流通体系,重点对新生代农户开展信息技术培训,提升其信息获取能力。

Inverse procedure for determining model parameter of soils using real-coded genetic algorithm

The hybrid genetic algorithm is utilized to facilitate model parameter estimation.The tri-dimensional compression tests of soil are performed to supply experimental data for identifying nonlinear constitutive model of soil.In order to save computing time during parameter inversion,a new procedure to compute the calculated strains is presented by multi-linear simplification approach instead of finite element method(FEM).The real-coded hybrid genetic algorithm is developed by combining normal genetic algorithm with gradient-based optimization algorithm.The numerical and experimental results for conditioned soil are compared.The forecast strains based on identified nonlinear constitutive model of soil agree well with observed ones.The effectiveness and accuracy of proposed parameter estimation approach are validated.

Mixing matrix estimation of underdetermined blind source separation based on the linear aggregation characteristic of observation signals

Under the underdetermined blind sources separation(UBSS) circumstance,it is difficult to estimate the mixing matrix with high-precision because of unknown sparsity of signals.The mixing matrix estimation is proposed based on linear aggregation degree of signal scatter plot without knowing sparsity,and the linear aggregation degree evaluation of observed signals is presented which obeys generalized Gaussian distribution(GGD).Both the GGD shape parameter and the signals' correlation features affect the observation signals sparsity and further affected the directionality of time-frequency scatter plot.So a new mixing matrix estimation method is proposed for different sparsity degrees,which especially focuses on unclear directionality of scatter plot and weak linear aggregation degree.Firstly,the direction of coefficient scatter plot by time-frequency transform is improved and then the single source coefficients in the case of weak linear clustering is processed finally the improved K-means clustering is applied to achieve the estimation of mixing matrix.The proposed algorithm reduces the requirements of signals sparsity and independence,and the mixing matrix can be estimated with high accuracy.The simulation results show the feasibility and effectiveness of the algorithm.

Hybrid Differential Evolution for Estimation of Kinetic Parameters for Biochemical Systems

Determination of the optimal model parameters for biochemical systems is a time consuming iterative process. In this study, a novel hybrid differential evolution （DE） algorithm based on the differential evolution technique and a local search strategy is developed for solving kinetic parameter estimation problems. By combining the merits of DE with Gauss-Newton method, the proposed hybrid approach employs a DE algorithm for identifying promising regions of the solution space followed by use of Gauss-Newton method to determine the optimum in the identified regions. Some well-known benchmark estimation problems are utilized to test the efficiency and the robustness of the proposed algorithm compared to other methods in literature. The comparison indicates that the present hybrid algorithm outperforms other estimation techniques in terms of the global searching ability and the con- vergence speed. Additionally, the estimation of kinetic model parameters for a feed batch fermentor is carried out to test the applicability of the proposed algorithm. The result suggests that the method can be used to estimate suitable values of model oarameters for a comolex mathematical model.

A posteriori error estimator for eigenvalue problems by mixed finite element method

In this paper,a residual type of a posteriori error estimator for the general second order elliptic eigenpair approximation by the mixed finite element method is derived and analyzed,based on a type of superconvergence result of the eigenfunction approximation.Its efficiency and reliability are proved by both theoretical analysis and numerical experiments.

A combined mixed finite element method and local discontinuous Galerkin method for miscible displacement problem in porous media

A combined method consisting of the mixed finite element method for flow and the local discontinuous Galerkin method for transport is introduced for the one-dimensional coupled system of incompressible miscible displacement problem. Optimal error estimates in L∞(0,T;L2) for concentration c,in L2(0,T;L2)for cxand L∞(0,T;L2) for velocity u are derived. The main technical difficulties in the analysis include the treatment of the inter-element jump terms which arise from the discontinuous nature of the numerical method,the nonlinearity,and the coupling of the models. Numerical experiments are performed to verify the theoretical results. Finally,we apply this method to the one-dimensional compressible miscible displacement problem and give the numerical experiments to confirm the efficiency of the scheme.