基于交通信号灯信息的混合动力汽车节能预测控制方法

针对传统混合动力汽车控制方法不考虑已知道路交通信号灯信息对车辆能量管理影响的问题,提出了基于交通信号灯信息的混合动力汽车节能预测控制智能优化策略。通过建立混合动力汽车系统的简化模型,并采用连续广义最小残量方法求解模型预测控制问题。运用MATLAB/Simulink进行仿真,仿真结果验证了交通信号灯信息模型的有效性,以及所设计的模型预测控制算法大幅度提高混合动力汽车的燃油经济性的能力和实时控制性能。研究结果表明所提出的控制策略可以实现车辆行驶轨迹的优化控制,显著提高了车辆的燃油经济性,并满足系统的实时最优控制要求。     

雷电波分析与比较研究

本文对双指数雷电流模型和 IEC1 3 1 2—— 1推荐的雷电流模型进行了分析和研究 ,计算了这两种雷电流模型的雷电流参数。在此基础上 ,用 FFT方法分析了雷电流的频谱分布     

女大学生排球选修课教学之我见

本文依据大学生生理、心理的阶段特征，通过变换组织教法以及增强学生主体、教师主导的双边作用，分析排球课的项目特点。使技能学习和人格发展相结合，培养身心健康发展的大学生。     

基于WEB方式的电子政务初探

本提出了基于WEB方式的电子政务设计、开发、运营方法和技术平台的总体框架。描述了电子政务数据开发模型的雄度，电子政务系统工程的实施原则、实施步骤及应用系统集成的一整套的实践模型。     

线性回归分析与能源需求预测

结合实例介绍了回归模型方法在能源预测中的应用，具体地讨论了最简单、最基本的直线回归模型结构及参数估计方法，对于其他一些曲线回归模型则可通过变量代换转化为直线回归模型。     

电磁场中带电粒子束运动的力学模拟

研究以不同初速度进入互相垂直的匀强磁场和均强电场中的带电粒子束的运动情形，并同相似的力学运动相比拟，建立了直观的力学模型。     

期权理论在高新企业价值评估中的应用

分析了高新技术企业特点，说明了传统的企业价值评估方法不能应用于对高新技术企业的评估。如果把高新技术企业投资看成是为了获得一个未来取得现金流的机会，高新技术企业具有期权性质，就可以用期权理论及Black-Scholes模型评估高新企业的价值。     

Lagrangian for the t–J Model Constructed from the Generators of the Supersymmetric Hubbard Algebra

In order to describe the dynamics of the t–J model, two different families of first-order Lagrangians in terms of the generators of the Hubbard algebra are found. Such families correspond to different dynamical second-class constrained systems. The quantization is carried out by using the path-integral formalism. In this context the introduction of proper ghost fields is needed to render the model renormalizable. In each case the standard Feynman diagrammatics is obtained and the renormalized physical quantities are computed and analyzed. In the first case a nonperturbative large-N expansion is considered with the purpose of studying the generalized Hubbard model describing N-fold-degenerate correlated bands. In this case the 1/N correction to the renormalized boson propagator is computed. In the second case the perturbative Lagrangian formalism is developed and it is shown how propagators and vertices can be renormalized to each order. In particular, the renormalized ferromagnetic magnon propagator coming from our formalism is studied in details. As an example the thermal softening of the magnon frequency is computed. The antiferromagnetic case is also analyzed, and the results are confronted with previous one obtained by means of the spin-polaron theories.     

Linearization of column responses by correlation chromatography. Separation improvement and reduction of undesired adsorption effects

Summary Experiments and simulations prove that correlation chromatography can greatly reduce the disadvantage of a non-linear response of the chromatographic column. A factor that has been accepted as being an important source of error in correlation or multiplex chromatography, has been shown not to be. Separations affected, improve dramatically when correlation chromatography is used, and a substantial amount of correlation noise only arises when there is a large difference in separation between a conventional chromatogram and a correlogram.A model has been developed for simulating these nonlinearities. It is shown that, especially for correlation chromatography, the simulation results match the practical measurements very well.     

Recursive partition and amalgamation with the exponential family: Theory and applications

The theory of tree-growing (RECPAM approach) is developed for outcome variables which are distributed as the canonical exponential family. The general RECPAM approach (consisting of three steps: recursive partition, pruning and amalgamation), is reviewed. This is seen as constructing a partition with maximal information content about a parameter to be predicted, followed by simplification by the elimination of ‘negligible’ information. The measure of information is defined for an exponential family outcome as a deviance difference, and appropriate modifications of pruning and amalgamation rules are discussed. It is further shown how the proposed approach makes it possible to develop tree-growing for situations usually treated by generalized linear models (GLIM). In particular, Poisson and logistic regression can be tree-structured. Moreover, censored survival data can be treated, as in GLIM, by observing a formal equivalence of the likelihood under random censoring and an appropriate Poisson model. Three examples are given of application to Poisson, binary and censored survival data.