Accuracy in forecasting: A survey

In this study, the author provides a brief and concise summary of empirical investigations pertaining to forecasting with special reference to the accuracy of different forecasting techniques. The study mainly focuses on comparisons of the accuracy of these techniques. The comparisons cover both quantitative and qualitative methods. In addition the summary includes studies seeking to test or improve accuracy by combining forecasting techniques.     

The accuracy of extrapolation (time series) methods: Results of a forecasting competition

In the last few decades many methods have become available for forecasting. As always, when alternatives exist, choices need to be made so that an appropriate forecasting method can be selected and used for the specific situation being considered. This paper reports the results of a forecasting competition that provides information to facilitate such choice. Seven experts in each of the 24 methods forecasted up to 1001 series for six up to eighteen time horizons. The results of the competition are presented in this paper whose purpose is to provide empirical evidence about differences found to exist among the various extrapolative (time series) methods used in the competition.     

Time-series analysis supported by power transformations

This paper presents some procedures aimed at helping an applied time-series analyst in the use of power transformations. Two methods are proposed for selecting a variance-stabilizing transformation and another for bias-reduction of the forecast in the original scale. Since these methods are essentially model-independent, they can be employed with practically any type of time-series model. Some comparisons are made with other methods currently available and it is shown that those proposed here are either easier to apply or are more general, with a performance similar to or better than other competing procedures.     

2016年我国物价形势分析及2017年展望

2016年,我国居民消费价格指数（CPI）同比涨幅呈“前高中低后升”的运行特征,消费领域价格涨幅总体温和,工业生产者价格指数（PPI）同比由负转正,生产领域通缩压力逐步缓和,预计2016年CPI上涨2.0%,PPI下降1.7%。展望2017年,宽松的金融货币环境、人力成本趋势性上升、翘尾因素升高、猪肉价格走势存在不确定性等因素将支撑价格上涨,总需求稳中趋缓、农业领域粮食产量和库存双高、以房地产为代表的资产价格稳中有降、通胀预期偏弱等因素将抑制物价涨幅。综合考虑诸上因素的影响,预计2017年CPI上涨1.8%,PPI上涨1.0%。因此,本文建议实施灵活稳健的货币政策、做好农业生产保障主要农产品供给稳定、多措并举扩大去产能范围、稳步推进能源资源和服务等领域价格改革、因城施策稳定房地产市场价格和预期,助推供给侧结构性改革。     

Neural network versus econometric models in forecasting inflation

Artificial neural network modelling has recently attracted much attention as a new technique for estimation and forecasting in economics and finance. The chief advantages of this new approach are that such models can usually find a solution for very complex problems, and that they are free from the assumption of linearity that is often adopted to make the traditional methods tractable. In this paper we compare the performance of Back‐Propagation Artificial Neural Network (BPN) models with the traditional econometric approaches to forecasting the inflation rate. Of the traditional econometric models we use a structural reduced‐form model, an ARIMA model, a vector autoregressive model, and a Bayesian vector autoregression model. We compare each econometric model with a hybrid BPN model which uses the same set of variables. Dynamic forecasts are compared for three different horizons: one, three and twelve months ahead. Root mean squared errors and mean absolute errors are used to compare quality of forecasts. The results show the hybrid BPN models are able to forecast as well as all the traditional econometric methods, and to outperform them in some cases. Copyright © 2000 John Wiley & Sons, Ltd.     

2020年经济景气形势监测、分析和预测

2020年1季度新冠肺炎疫情给经济和社会带来前所未有的冲击,使经济景气出现了断崖式大幅下降,警情指数罕见发出“过冷”信号,但2、3季度经济景气明显回暖,9月已经回到“正常”区间。经济周期已经在2020年2月形成改革开放以来的最低收缩谷底,从3月开始经济景气进入新一轮周期的扩张期。预计4季度GDP增速将继续回升至潜在增长水平附近,全年经济增长2.3%左右,CPI上涨2.7%左右。宏观调控应继续以“保就业、促消费、稳投资”为主要政策发力点,推进落实“六稳”、“六保”政策,使经济增长回归并保持在潜在增长率水平附近;同时需提前关注和应对经济金融领域的多种风险,平衡好稳增长和防风险。     

基于加权余弦相似度与极限学习机的电力负荷短期预测

为提高电力系统管理的效率,提出一种基于加权余弦相似度与极限学习机(extreme tearning machine, ELM)的电力负荷短期预测设计。通过熵权法对电力负荷相关物理信息进行权重分配,获得的权重赋予到余弦相似度中,利用加权余弦相似度对历史日与待测日的电负荷数据进行相似度选取,筛选数据作为极限学习机的输入,提高极限学习机回归模型的精度,最终获取电力负荷预测。实验分析与反向传播BP(back propagation)神经网络、支持向量机(spupport vector machine, SVM)预测算法对比,该方法能有效提高预测模型的精度,同时简化计算量。     

影视未来学与科学预演影片初论

目前从产业经济的角度看,影视业是比较成功的,但是从满足社会发展的角度看,影视产品还远没有发挥应有的作用,认识功能和教化功能还十分薄弱。本文提出创建＂影视未来学＂、＂影视战略学＂、＂影视预测学＂、＂情景未来学＂、＂情景预测学＂和＂科学预测影片＂、＂科学预演影片＂等,力图利用影视的预演手段,实现和增强影视的认识和教化功能,推动创意产业和学术研究的进步。     

直流电法技术在矿井防治水中的应用

介绍了矿井直流电法超前探测技术的原理与方法,并以晋城凤凰山矿北翼探巷矿井直流电法探测为例,分析了矿井直流电法在探测巷道前方岩层富水区中的应用。通过井下探放水钻孔及实际揭露资料验证,该方法探测采掘工作面前方富水位置和范围是非常有效的物探方法之一,能为井下水害预报和防治提供可靠依据。     

基于微分方程数值解的灰色预测建模

灰色预测建模方法较多,预测精度主要取决于模型参数的估计,本文给出一种新的思想,将已知的观测值看作是微分方程在不同结点(时间)处的近似解,利用微分方程数值解法推算公式,使用最小二乘法原理,让其局部截断误差的平方和最小来估计未知参数,进而建立灰色预测模型。实例表明,本方法预测精度高。