成都市温江区经济发展趋势分析与预测

依据客观历史统计数据,对成都市温江区经济发展过程中的各主要经济指标及其相关的重要因素进行研究,建立了这些主要经济指标与相关重要因素之间的线性或非线性的关联,得到了相应的预测结果:在未来数年内,温江区GDP仍将快速攀升,固定资产投资规模迅速扩大,工业经济效益明显增加,农业总产值与农民人均纯收入增幅显著,财政总收入与第三产业产值稳步提升。指出温江区应继续妥善贯彻“强二、优一、兴三”的产业政策,推动全区经济快速、有序发展和社会的全面进步。     

Correcting the January optimism effect

Each month, various professional forecasters give forecasts for next year's real gross domestic product (GDP) growth and unemployment. January is a special month, when the forecast horizon moves to the following calendar year. Instead of deleting the January data when analyzing forecast updates, I propose a periodic version of a test regression for weak-form efficiency. An application of this periodic model for many forecasts across a range of countries shows that in January GDP forecast updates are positive, whereas the forecast updates for unemployment are negative. I document that this January optimism about the new calendar year is detrimental to forecast accuracy. To empirically analyze Okun's law, I also propose a periodic test regression, and its application provides more support for this law.     

周期性需求下多级库存缺货控制模型研究

从一个以区域分销中心(DC)为主导地位且由多个供应商与零售商共同组成的多级库存系统出发,系统在假设DC和零售商都实行连续性盘点的(R,Q)库存控制策略,提前期为常量,零售商需求为正态分布的前提下,采用缺货策略的思想来确定订货临界点及订货批量.并且以确定DC的库存策略为目标,建立了缺货条件下的多级库存控制模型,从而达到有效控制库存的目的.最后,给出了一个算例,说明了该库存控制模型的可行度.     

分形理论在吉林西部干旱指数预测中的应用

干旱指数反映了气候的干旱程度,干旱指数的年际变化能够体现一个地区气候的演变.吉林西部降水不足,蒸发量大,干旱程度逐渐加剧.应用分形理论,首先进行了吉林西部1951-2003年共53 a干旱指数的R/ S分析,计算出Hurst系数,结果表明吉林西部的干旱指数在时间序列上具有显著的自相似性.在此基础上,应用连续变维分形模型预测了2004-2023年的干旱指数,结果表明该区气候将继续向干旱的趋势发展.     

Does a lot help a lot? Forecasting stock returns with pooling strategies in a data‐rich environment

A variety of recent studies provide a skeptical view on the predictability of stock returns. Empirical evidence shows that most prediction models suffer from a loss of information, model uncertainty, and structural instability by relying on low‐dimensional information sets. In this study, we evaluate the predictive ability of various lately refined forecasting strategies, which handle these issues by incorporating information from many potential predictor variables simultaneously. We investigate whether forecasting strategies that (i) combine information and (ii) combine individual forecasts are useful to predict US stock returns, that is, the market excess return, size, value, and the momentum premium. Our results show that methods combining information have remarkable in‐sample predictive ability. However, the out‐of‐sample performance suffers from highly volatile forecast errors. Forecast combinations face a better bias–efficiency trade‐off, yielding a consistently superior forecast performance for the market excess return and the size premium even after the 1970s.     

Forecasting the duration of short‐term deflation episodes

The paper proposes a simulation‐based approach to multistep probabilistic forecasting, applied for predicting the probability and duration of negative inflation. The essence of this approach is in counting runs simulated from a multivariate distribution representing the probabilistic forecasts, which enters the negative inflation regime. The marginal distributions of forecasts are estimated using the series of past forecast errors, and the joint distribution is obtained by a multivariate copula approach. This technique is applied for estimating the probability of negative inflation in China and its expected duration, with the marginal distributions computed by fitting weighted skew‐normal and two‐piece normal distributions to autoregressive moving average ex post forecast errors and using the multivariate Student t copula.     

高斯白噪声背景下机动目标未来运动状态的一步实时预报与滤波

对高斯白噪声背景下机动目标的运动共性进行了研究,绕过了建立系统加速度模型的麻烦,得到了未来运动趋势的一步实时预报模型,并具有很好的实时性.文章中还给出了算例与仿真计算结果.     

故障模糊预测系统开发环境的思想及其实现

针对故障诊断的现状和发展,本文探讨了故障模糊预测系统的开发环境,并研究了系统的知识表达方式和推理控制策略。     

基于自适应神经网络的边坡位移预测

通过对边坡位移历史数据序列进行特征分析 ,计算出饱和嵌入维数和最大 Lyapunov指数 ,给出了边坡位移的最大可预报时间尺度。在此基础上 ,确定了神经网络的输入节点数 ,建立了基于自适应神经网络的边坡位移预报方法 .通过对三峡升船机高边坡和新滩滑坡实际位移数据进行预测 ,结果令人满意 .这对于建立边坡位移的实时监测 -预警系统有重要意义.     

洪水预报误差分布的极大熵法

首先根据实际洪水预报误差出现在有限区域的特点,应用极大熵原理,建立了洪水总量预报误差分布的极大熵模型;通过几个不同流域的计算,得出随着降雨量的增大,产流预报误差趋于一个稳定值的结论. 同时将该模型计算的分布与正态分布进行了比较,结果表明用极大熵法求得的误差概率分布能更好地描述洪水总量预报误差的分布特性,可以根据实际降雨量的大小确定不同的最大不确定性的误差分布,为分析不同量级洪水预报的风险提供依据.