Propagation factors of Hermite–Gaussian beams in turbulent atmosphere

Based on the extended Huygens–Fresnel integral and the second-order moments of the Wigner distribution function, an analytical formulae for the propagation factors (M²-factors) of coherent and partially coherent one-dimensional Hermite–Gaussian beams in a turbulent atmosphere are derived. Evolution properties of the M²-factor of the Hermite–Gaussian beam in a turbulent atmosphere are studied numerically in detail. Our results show that the M²-factor of the Hermite–Gaussian beam increases upon propagation in a turbulent atmosphere. The M²-factor of the Hermite–Gaussian beam with larger beam order (or lower coherence) increases slower that of the Hermite–Gaussian beam with smaller beam order (or higher coherence) in a turbulent atmosphere, which means that the Hermite–Gaussian beam with a larger beam order and lower coherence is less affected by a turbulent atmosphere. Our results will be useful in long-distance free-space optical communications.     

The characteristics analysis of a new-style four-mirror axisymmetric-fold-combination cavity adapting to cylindrical discharge region

An axisymmetric-fold-combination (ASFC) cavity composed of two planar mirrors and spherical mirrors was designed. It is a stable-unstable resonator cavity. The light field of radial direction is Gaussian distribution. And in angular orientation, the distribution keeps invariant. It could generate annular CO₂ laser beam with excellent spatial coherence. And the spatial coherence is commendably realized with its stable-unstable cavity structure. The output light intensity distribution of this special model was discussed and simulated. With exterior lenses group, the output beams can be adjusted and controlled better to meet the manufactural requirements. Some references were provided for further research of the cavity with cylindrical discharge region.     

A BSDE-based approach for the optimal reinsurance problem under partial information

We investigate the optimal reinsurance problem under the criterion of maximizing the expected utility of terminal wealth when the insurance company has restricted information on the loss process. We propose a risk model with claim arrival intensity and claim sizes distribution affected by an unobservable environmental stochastic factor. By filtering techniques (with marked point process observations), we reduce the original problem to an equivalent stochastic control problem under full information. Since the classical Hamilton–Jacobi–Bellman approach does not apply, due to the infinite dimensionality of the filter, we choose an alternative approach based on Backward Stochastic Differential Equations (BSDEs). Precisely, we characterize the value process and the optimal reinsurance strategy in terms of the unique solution to a BSDE driven by a marked point process.     

基于Adaboost-SVR模型的我国碳排放强度分析与预测

首先对我国1960-2017年的碳排放趋势分5个阶段分析,发现虽然在不同时期存在波动,但长期来看,我国碳排放强度呈逐步下降趋势.然后对差分平稳后的序列数据建立Adaboost-SVR预测模型,采用RMSE、MAPE、MAE、MSE四个评价指标比较Adaboost-SVR模型与Adaboost-DT、SVR、BP神经网络对碳排放强度的预测精度.结果表明,组合模型明显优于其他3种模型,对于碳排放强度预测具有很高的可靠性.另外,通过使用Adaboost-SVR模型进行后续年份预测,发现我国未来碳排放强度总体将继续缓慢下降.最后,基于二氧化碳排放量的LMID分解结果,提出调整能源产业结构, 促进可再生能源利用等节能减排建议.     

基于改进的粒子群算法求解供应链网络均衡问题

传统的供应链求解方法为投影法,针对其要对投影进行计算,十分复杂的缺点,提出用改进的粒子群算法求解供应链均衡问题,利用动态异步调整学习因子来有效的提高了算法搜索能力与精度。本文介绍了供应链网络均衡问题转变为无约束优化问题的方法,然后用改进的粒子群优化算法进行求解。通过四个数值算例,将实验结果与标准粒子群算法、蜂群算法、学习因子同步变化的粒子群算法进行比较,验证了改进的粒子群优化算法在解决供应链网络均衡问题中的有效性与优越性,为供应链网络求解提供了一种新的方法。     

优化能源消费结构对河北省碳强度目标实现的贡献潜力分析

本文首先运用情景预测方法预测河北省未来地区生产总值和能源消费总量;然后构建马尔科夫链模型预测河北省未来能源消费结构,并对计算的平均转移概率矩阵进行优化;最后分不同组合情景评估能源消费结构优化对河北省二氧化碳排放强度目标的贡献潜力。结果表明:各种组合情景能源消费结构调整都能在不同程度上促进碳强度下降,对实现碳强度目标具有不同程度的贡献潜力。但是,在最理想状态下贡献潜力也只有16.7%~17.8%。因此,能源消费结构优化对碳强度目标贡献潜力作用有限,仅依靠能源结构优化无法完全实现碳强度目标,必须靠政府、企业以及社会各界一致努力,采取一系列对策才能顺利实现河北省“十三五”能源规划中制定的碳强度目标。     

Rotational tools for factor analytic models

Rotational ambiguity is a major problem in the application of factor analysis to a variety of multivariate mixture resolution problems and particularly important in the analysis of environmental data. As part of the development of an implementation of positive matrix factorization for the U.S. Environmental Protection Agency to distribute in support of airborne particle source identification and apportionment, several tools have been developed to control the rotations and explore the extent of rotational solution space. This discussion of the nature of the rotational tools provides an understanding of these rotational tools as well as the basis for their incorporation into other implementations of least‐squares based solutions to the factor analysis problem. Several example algorithms are presented. Copyright © 2008 John Wiley & Sons, Ltd.     

Parallel vector analysis based soft resolution of spectral data from pH‐metric titration using symmetry constraint

In this study, a soft method is proposed to calculate concentration and spectral profiles for the two‐way spectral data from dissociation equilibria of polyprotic acids (H_nA). This method has four main distinct steps: (i) a fixed size moving window evolving factor analysis (FSMWEFA) was used to identify the local rank map, (ii) WFA was applied to calculate the concentration profiles of H_nA and Aⁿ⁻ (selection of the window for application of WFA was performed using EFA), (iii) PVA was used to calculate H_{n − 1}A to HA spectral profiles, and (iv) a symmetry constraint, in addition to the non‐negativity constraint, was utilized to obtain the unique concentration and spectral profiles from different acceptable sets of profiles. In the absence of any selective region in the spectral data, the proposed soft method resulted in unique solution without rotational ambiguity. This study is the first application of symmetry constraint on concentration profiles. The rotational ambiguity drastically decreased on considering the constraint of symmetry of the H_{n − 1}A and HA concentration profiles, in addition to non‐negativity of profiles. Simulated examples were used to confirm these approaches. Effect of closeness of dissociation constants on the estimated values of constants was investigated. The results showed that when the difference between pK_a values is more than 1.2, the obtained errors in the estimation of pK_a values are less than about 6.5%. The considered real data were from pH‐metric titration of fluorescein. The obtained spectral and concentration profiles and the estimated pK_a values for fluorescein were in good agreement with the previously reported data. Copyright © 2009 John Wiley & Sons, Ltd.     

供需模型在众包平台定价中的应用

以众包平台为对象,基于已有数据,考虑供求关系,通过因子分析法对原始数据加以处理,建立任务的定价模型.在实际应用中,可以对分布密集的任务进行打包,并给出针对这种情况的定价模型.结果表明:提出的模型不仅考虑了会员人数与任务数量的关系,还考虑了个人需求的差异,提高了任务的完成度,对众包平台定价的发展与完善有着重要的意义.     

不良贷款约束下我国上市商业银行全要素生产率时序演变及其驱动因素研究——基于非期望产出的Malmquist-luenberger和Tobit模型

基于我国上市商业银行2007~2013年面板数据,构建包括不良贷款约束条件下我国上市商业银行投入产出指标体系,采用基于非期望产出的M-L生产率指数方法对我国上市商业银行全要素生产率跨期动态变化进行实证测度,并应用Tobit回归分析方法对影响我国上市商业银行全要素生产率的因素进行实证分析,实证结果显示:我国上市商业银行全要素生产率平均增长率为2.4%,上市城市商业银行全要素生产率高于股份制上市商业银行,而股份制商业银行高于国有商业银行,其主要来源与规模效率提升;此外,银行规模和存贷比对商业银行技术效率提升产生显著的正向驱动影响;而银行集中度对其产生显著的负向驱动影响;资产收益率和所有权结构对其影响不显著。