Forecast of telephonometry of Xiqing District using chaos time series

The telecommunication industry has marched into telephonometry competition age. In order to forecast telephonometry development, an effective method by using the chaos time series is proposed. And the best estimate method is presented by contrasted with mature and advanced estimate methods as follows： the stochastic forest, stochastic gradient boosting, the support vector and artificial neuron network.     

“十五”期间我国沥青应用预测

介绍了沥青的生产和需求现状，并根据消费行为的情况对沥青的市场和价格走势进行预测，分析了国内沥青行业的存在问题。     

The Nested PIGLOG Model: An Application to U.S. Food Demand

A new demand system is introduced, the Nested PIGLOG model, nesting thirteen other demand systems including five that are also new. This new model and its nested special cases are applied to models of U.S. food demand that include food-at-home (FAH), food-away-from-home (FAFH), and alcoholic beverages. Although nested tests and out-of-sample forecasting performance favor generalizing models to a certain degree, statistically insignificant improvements to in-sample-fit and even poorer out-of-sample forecast accuracy undermine further generalizations. Based on a subset of preferred models, FAFH is found to be price and income elastic compared to FAH which is price and income inelastic.     

The market’s view on the probability of banking sector failure: cross-country comparisons

Hall and Miles (1990) suggest an approach of estimating default probabilities of banks using stock market information, and in this paper we apply an aggregated version of their approach to banking sectors around the world in both developed and emerging economies. We study the market’s assessment of the probability of systemic banking crises world wide over the last decade, including the Asian crisis 1997–1998. In addition, we investigate whether there is a relationship between the failure probability and institutional features of the actual banking sector. The quality of governance and the degree of law and order in a country is found to be significantly negatively related to the market based failure probabilities as is an explicit deposit insurance during periods of crisis.     

面向售后服务的汽车备品需求预测研究

根据面向售后服务的汽车备品需求特点的差异,本文将其分为专用配件和通用配件并分别选用不同的预测模型.对专用配件,采用基于时间序列相关的线性回归模型,并运用加权最小二乘法（WLS）估计参数.对通用配件,选用GM（1,1）模型进行需求预测.     

基于顾客导向的物流企业风险预警

文中通过回顾企业风险预警管理相关文献,分析了物流企业风险形成主要影响因素,并结合物流企业运营特征,建立基于顾客导向的物流企业预警指标体系,运用灰关联分析方法评价物流企业顾客满意度,对物流企业的风险进行预警。     

基于Markov链的物流园区需求灰色预测模型改进

物流因区是一项大型基础设施投资项目，在规划与设计上需要有一定的超前意识，而需求预测则是园区规划超前意识的重要依据。目前。国内外对物流园区需求预测方法的研究和实践基本上还处于发展阶段．至今尚未形成完整科学、操作性强的方法体系，现有的需求预测大体上是借鉴史通运输规划的模型．进行研究的过程中灰色模型预测有局限性。其预测结果与真实值之间存在一定误差，因而可以考虑利用Markov链提出改进方案。     

基于Web和数据仓库的房地产市场预警预报系统研究

介绍了基于Web和数据仓库的房地产市场预警预报系统的体系结构，探索设计了房地产市场预警预报系统的技术与方法，并提出了基于Web和数据仓库的房地产市场预警预报系统的完整解决方案。     

人工神经网络技术在物流需求量预测中的应用

运用人工神经网络模拟人脑的思维过程,建立了多个变量之间的非线性模型,从而为准确预测物流需求量提供了科学的依据。     

未来中国经济仍有较强稳定性

未来中国经济的稳定性是全社会关注的一个焦点。从国际、国内形势看，中国经济至少在未来5年内具有较强的稳定性。