基于EMD与DVG的非线性时间序列预测模型及其应用研究

针对具有非线性和不稳定性的时间序列,提出一种结合经验模态分解(EMD)、有向可见图(DVG)网络的动态预测模型。利用经验模态分解将原时间序列分解为多个固有模态函数(IMF),然后对分解后的高频和低频IMF利用快速傅里叶变换得到各自的周期;依据每个周期,从原时间序列的尾部截取长短不一的子序列,然后采用有向可见图算法转换为多个有向网络,利用随机游走在每个有向网络中寻找与时间序列最后一个节点相似的节点;最后,依据平行线法,预测时间序列的下一个数值。原油价格的时间序列是一类典型的具有非线性和不稳定性的序列,利用此模型对WTI原油每日价格进行实证分析。研究结果表明,此模型不但可以有效地预测时间序列的变化趋势,而且具有较高的预测精度。     

手机App列表信息在信用风险评价中的应用——基于互联网借贷平台的实证研究

随着互联网的发展和智能手机的普及,用户手机数据被用来评估借款人的信用风险,使用到的数据有通讯记录、短信息接发、移动轨迹、用户行为数据等,而本文研究了手机上所安装的App列表和借款人信用风险之间的关系。通过对某大型互联网借贷平台上的个人借贷数据以及借款人手机上安装的App列表数据的分析发现,手机上安装的App和借款人的信用状况存在关联关系。安装生活类、金融类和买房买车类App的借款人比没有安装这些App的借款人信用风险低;其中,记账类App、外卖类App、股票类App和买房类App对借款人的信用风险有较强的识别能力。把手机App列表信息加入信用风险评价模型之后,信用风险评价模型的区分能力得到显著提高。     

Ecological Risk Assessment,Prediction, and Assessing Risk Predictions

Ecological risk assessment embodied in an adaptive management framework is becoming the global standard approach for formally assessing and managing the ecological risks of technology and development. Ensuring the continual improvement of ecological risk assessment approaches is partly achieved through the dissemination of not only the types of risk assessment approaches used, but also their efficacy. While there is an increasing body of literature describing the results of general comparisons between alternate risk assessment methods and models, there is a paucity of literature that post hoc assesses the performance of specific predictions based on an assessment of risk and the effectiveness of the particular model used to predict the risk. This is especially the case where risk assessments have been used to grant consent or approval for the construction of major infrastructure projects. While postconstruction environmental monitoring is increasingly commonplace, it is not common for a postconstruction assessment of the accuracy and performance of the ecological risk assessment and underpinning model to be undertaken. Without this “assessment of the assessment,” it is difficult for other practitioners to gain insight into the performance of the approach and models used and therefore, as argued here, this limits the rate of improvement of risk assessment approaches.     

商业银行信用风险及评估方法应用述评

信用风险是商业银行面临的最主要的风险，如何改进信用风险评估方法、提高预测精度是摆在学术界和实践界的重要课题。自20世纪30年代以来，商业银行信用风险的评估方法大致经历了比例分析、统计分析和人工智能三个阶段。在对风险、信用风险概念分析的基础上，对主要的信用风险评估方法进行述评。     

基于Haar小波变换的无失真图像压缩

提出了一种利用Ｈａａｒ小波进行图像无失真压缩的算法。对线性预测后的图像进行Ｈａａｒ小波分解，将各子带小波系数根据大小分解成两部分，其位置信息分别通过自适应算术编码进行了有效的压缩。试验结果表明，该算法实现简单，达到了很好的压缩效果。     

Bayesian System Reliability Prediction

In system reliability studies a common problem is the coherent assessment of system reliability, based on generic database information from components and on failure data from a system and its components in a common, but unknown, environment. A solution to this problem is given.     

西安市入境旅游市场特征及趋势预测研究

以西安市为例，运用定量分析方法，从总体特征、时间结构、空间结构、消费结构等方面对2001-2006年入境旅游市场进行分析，得出西安市入境旅游人数和旅游外汇收入在绝对值上保持较快增长，但是和全国总量以及其他旅游城市相比，市场优势地位并不明显，产业地位逐渐下降等结论。根据西安市1978-2006年的入境游客人数和旅游外汇收入数据做回归拟和，预测未来5年，西安市入境游客人数和旅游外汇收入将保持稳定增长，并提出拓展入境旅游市场的相关对策。     

社会保障制度改革的回顾与前瞻

改革开放30年来，我国在养老保险、医疗保险、失业保险、社会救助、农村社会保障制度等方面进行了深入的探索，初步建立起与市场经济体制相适应的社会保障制度，但我们还必须从社会保障的法制建设、建立多层次的社会保障体系、多渠道筹集社会保障基金、社会保障的监管等方面加以完善。     

Penalized contrast estimation in functional linear models with circular data

Our aim is to estimate the unknown slope function in the functional linear model when the response Y is real and the random function X is a second-order stationary and periodic process. We obtain our estimator by minimizing a standard (and very simple) mean-square contrast on linear finite dimensional spaces spanned by trigonometric bases. Our approach provides a penalization procedure which allows to automatically select the adequate dimension, in a non-asymptotic point of view. In fact, we can show that our penalized estimator reaches the optimal (minimax) rate of convergence in the sense of the prediction error. We complete the theoretical results by a simulation study and a real example that illustrates how the procedure works in practice.     

一致性分数阶优化灰色模型及其应用

传统的分数阶灰色预测模型在时间序列预测中具有较好的适应性和预测的有效性,但其累加和差分计算式比较复杂。一致性分数阶累加相对于一般的分数阶累加,形式更简单,更便于计算和理论推导。为了提高模型的适应性和预测能力,文章在CFGM(1,1)白化方程中引入一个新的可变系数,扩大了原有白化方程的适用范围,并在此基础上构建了一致性分数阶优化灰色模型,即CFOGM(1,1)模型。最优一致性分数阶阶数和可变系数通过PSO算法最小化平均相对误差获得。将构建的模型运用到两个实例中并与其他经典的灰色预测模型进行对比,结果表明所提出的模型具有较高的拟合和预测精度。