Forecasting the urban skyline with extreme value theory

The world’s urban population is expected to grow fifty percent by the year 2050 and exceed six billion. The major challenges confronting cities, such as sustainability, safety, and equality, will depend on the infrastructure developed to accommodate the increase. Urban planners have long debated the consequences of vertical expansion—the concentration of residents by constructing tall buildings—over horizontal expansion—the dispersal of residents by extending urban boundaries. Yet relatively little work has predicted the vertical expansion of cities and quantified the likelihood and therefore urgency of these consequences.We regard tall buildings as random exceedances over a threshold and use extreme value theory to forecast the skyscrapers that will dominate the urban skyline in 2050 if present trends continue. We predict forty-one thousand skyscrapers will surpass 150 meters and 40 floors, an increase of eight percent a year, far outpacing the expected urban population growth of two percent a year. The typical tall skyscraper will not be noticeably taller, and the tallest will likely exceed one thousand meters but not one mile. If a mile-high skyscraper is constructed, it will hold fewer occupants than many of the mile-highs currently designed. We predict roughly three-quarters the number of floors of the Mile-High Tower, two-thirds of Next Tokyo’s Sky Mile Tower, and half the floors of Frank Lloyd Wright’s The Illinois—three prominent plans for a mile-high skyscraper. However, the relationship between floor and height will vary considerably across cities.     

产业集聚视阈下江西制造业有效承接长珠闽产业转移研究

科学分析长珠闽地区产业转移趋势和江西适宜承接的行业,对江西有效承接长珠闽产业转移具有重要的现实意义。通过产业集聚指数分析,长珠闽地区制造业整体向外转移趋势明显,但仍以劳动和资源密集型产业为主,广东、江苏和福建制造业向外转移相对滞后。为此,要利用江西地处长珠闽共同腹地优势,因地制宜地承接产业集聚强化行业和成长行业,积极培育战略性新兴产业,突出产业补链模式、内部提升模式、"飞地经济"模式、组团式模式和逆梯度模式,打造产业集聚品牌和优势,优化对接服务。     

Global energy forecasting competition 2017: Hierarchical probabilistic load forecasting

The Global Energy Forecasting Competition 2017 (GEFCom2017) attracted more than 300 students and professionals from over 30 countries for solving hierarchical probabilistic load forecasting problems. Of the series of global energy forecasting competitions that have been held, GEFCom2017 is the most challenging one to date: the first one to have a qualifying match, the first one to use hierarchical data with more than two levels, the first one to allow the usage of external data sources, the first one to ask for real-time ex-ante forecasts, and the longest one. This paper introduces the qualifying and final matches of GEFCom2017, summarizes the top-ranked methods, publishes the data used in the competition, and presents several reflections on the competition series and a vision for future energy forecasting competitions.     

从产业转移到产业集群形成的微观机理研究

产业转移与厂商重新选择厂址是连在一起的。多数厂商选择同一区位就可能导致产业的空间集聚,最终形成产业集群。从研究厂商选址到产业空间集聚的微观机理出发,深入研究厂商选址与产业集群的关系,揭示产业转移的内在原因,并从中得到我国如果实现产业转移的启示。     

基于IOWA算子的灰色—多项式组合模型在武汉市物流需求预测中的应用

针对2002～2009年武汉市物流需求的数据,采用灰色GM 1,1模型和多项式拟合模型两种单项预测模型对数据进行建模预测。并结合组合预测理论,采用基于IOWA算子的组合预测模型进行预测,结果表明基于诱导有序加权平均算子的组合预测模型的预测精度明显高于两种单项预测方法,说明了该方法用于物流需求预测的可行性和有效性,并在此基础上对2010～2012年的武汉市物流需求作出预测。     

产业结构变迁与中国OFDI：2003~2014年

本文采用2003~2014年187个中国对外直接投资国（地区）的跨境数据,实证分析了产业结构变迁及其引起的OFDI行业构成的变化对我国OFDI的影响效应。结果表明,产业结构合理化和高级化对OFDI均具有显著的正向影响,且两者之间对OFDI具有交互效应。在OFDI行业构成方面,信息传输、计算机服务和软件业与房地产业以及科学研究、技术服务和地质勘查业等三个行业占比的增加对OFDI具有显著的正向影响,农、林、牧、渔业与电力、燃气及水的生产和供应业等两个行业占比的增加对OFDI具有显著的负向影响,其他行业占比的增加对OFDI具有不同程度的影响。     

Beyond point forecasting: Evaluation of alternative prediction intervals for tourist arrivals

This paper evaluates the performances of prediction intervals generated from alternative time series models, in the context of tourism forecasting. The forecasting methods considered include the autoregressive (AR) model, the AR model using the bias-corrected bootstrap, seasonal ARIMA models, innovations state space models for exponential smoothing, and Harvey’s structural time series models. We use thirteen monthly time series for the number of tourist arrivals to Hong Kong and Australia. The mean coverage rates and widths of the alternative prediction intervals are evaluated in an empirical setting. It is found that all models produce satisfactory prediction intervals, except for the autoregressive model. In particular, those based on the bias-corrected bootstrap perform best in general, providing tight intervals with accurate coverage rates, especially when the forecast horizon is long.     

基于IOWA算子的组合预测模型在物流需求预测中的应用

根据2000~2009年宁波市物流需求的数据,采用灰色GM 1,,1,模型和一元线性回归模型进行组合优化,建立了基于诱导有序加权平均(IOWA)算子的物流需求量组合预测模型。结果表明基于IOWA算子的组合预测模型能有效提高预测精度,说明了该方法用于物流需求预测的可行性和有效性,并在此基础上对2010~2013年宁波市物流需求作出预测。     

矿业城市工业废弃地再开发策略研究

论文首先阐述矿业城市工业废弃地的概念,分析了工业废弃地的负面影响及其蕴含的资源价值,归纳了工业废弃地作为矿业城市新资源的潜在优势,引入资源"创新集成"概念,明确经济发展、社会稳定、文化延续、自然环境及城市体型环境综合提升的五个目标,最后探讨了矿业城市工业废弃地再开发的策略.     

改进灰色预测模型在我国船舶订单预测中的应用

面时人民币升值、钢材等原材料价格上涨、国际金融危机的冲击和市场出现的急剧变化，全年全国承接新船订单5818万载重吨．同比下降40．9％；手持船舶订单2．046亿载重吨，同比增长28．7％。未来几年，世界造船市场的需求如何，中国船舶制造企业该如何积极应对？这些都是中国造船业必须要面对和思考的问题。文章从手持订单量出发，借助改进后的灰色预测模型，对未来两年我国造船行业做一个简单预测，以期对我国造船业的发展提供借鉴和参考。     

基于“钻石模型”的上海创意产业竞争力评价研究

作为21世纪以知识要素为基础的新经济模式的支柱,创意产业（Creative Industry）在拉动地区经济增长,改变产业结构和促进就业,树立现代城市新形象中的重要作用正逐渐为人们所认识和关注。客观合理地评价一个产业的竞争力,对该产业的发展具有重要的意义。本文基于波特关于产业竞争力的钻石模型理论,结合上海创意产业的发展现状,对上海市创意产业的竞争力进行了分析和评价,并对如何提升上海创意产业竞争力提出了一些建议。     

The impact of institutional change on forecast accuracy: A case study of budget forecasting in Washington State

This paper explores the relationship between institutional change and forecast accuracy via an analysis of the entitlement caseload forecasting process in Washington State. This research extends the politics of forecasting literature beyond the current area of government revenue forecasting to include expenditure forecasting and introduces an in-depth longitudinal study to the existing set of cross-sectional studies. Employing a fixed-effects model and ordinary least squares regression analysis, this paper concludes that the establishment of an independent forecasting agency and subsequent formation of technical workgroups improve forecast accuracy. Additionally, this study finds that more frequent forecast revisions and structured domain knowledge improve forecast accuracy.     

产业集群的形态与演化评述

本文在全面回顾国外产业集聚理论及构建产业集群研究逻辑框架的基础上,按一定分类角度集中评述了产业集群的形态及其演化发展阶段。最后针对中国纺织产业的特性,重点阐述了其形态和演化发展现状并指明了专题研究意义。     

政府促进产业集群升级机理的agent仿真研究

运用产业集群理论及agent方法,从集群内部企业的行为入手,分析集群内企业对产业政策响应,建立产业集群—政府作用模型,研究政府制定政策对于促进产业集群升级的作用。在Simphony repast环境下,通过实证数据对产业政策对于促进产业集群升级的效果进行仿真,从而验证产业政策的有效性。     

The use of multiple scenarios in sales forecasting: An empirical test

Nearly 500 annual sales forecasts were generated from the responses of 82 subjects who were presented with either a time-series plot of historical sales data by itself or with the same plus three scenarios, and were then asked to make forecasts. Sales forecasts were made in either a stable or an unstable environment. The findings did not support the claims made by scenario advocates. Scenarios did not make unexpected outcomes less surprising. Instead, scenarios were found to increase confidence in a favored forecast. Furthermore, no support was found for the contention that scenarios improved upon ‘eyeball’ extrapolations or made judgmental sales forecasts more accurate than quantitative extrapolations. Scenarios were found to be tainted by many of the same biases previously identified by cognitive psychologists.     

基于组合模型的中长期电力负荷预测研究

本文研究了组合预测的模型,提高了预测的准确度。并对甘肃省2011-2020年全社会用电量做组合预测。     

The performance of the global bottom-up approach in the M5 accuracy competition: A robustness check

The M5 accuracy competition has presented a large-scale hierarchical forecasting problem in a realistic grocery retail setting in order to evaluate an extended range of forecasting methods, particularly those adopting machine learning. The top ranking solutions adopted a global bottom-up approach, by which is meant using global forecasting methods to generate bottom level forecasts in the hierarchy and then using a bottom-up strategy to obtain coherent forecasts for aggregate levels. However, whether the observed superior performance of the global bottom-up approach is robust over various test periods or only an accidental result, is an important question for retail forecasting researchers and practitioners. We conduct experiments to explore the robustness of the global bottom-up approach, and make comments on the efforts made by the top-ranking teams to improve the core approach. We find that the top-ranking global bottom-up approaches lack robustness across time periods in the M5 data. This inconsistent performance makes the M5 final rankings somewhat of a lottery. In future forecasting competitions, we suggest the use of multiple rolling test sets to evaluate the forecasting performance in order to reward robustly performing forecasting methods, a much needed characteristic in any application.     

A profitable model for predicting the over/under market in football

The over/under 2.5 goals betting market allows gamblers to bet on whether the total number of goals in a football match will exceed 2.5. In this paper, a set of ratings, named ‘Generalised Attacking Performance’ (GAP) ratings, are defined which measure the attacking and defensive performance of each team in a league. GAP ratings are used to forecast matches in ten European football leagues and their profitability is tested in the over/under market using two value betting strategies. GAP ratings with match statistics such as shots and shots on target as inputs are shown to yield better predictive value than the number of goals. An average profit of around 0.8 percent per bet taken is demonstrated over twelve years when using only shots and corners (and not goals) as inputs. The betting strategy is shown to be robust by comparing it to a random betting strategy.     

产业的集群化特征与集群式发展研究——基于中国投入产出的方法

20世纪90年代以来，中国国民经济体系中产业的集群化特征日益凸显。本文从投入产出的角度，识别中国国民经济中的产业集群，分析产业的集群化特征，在此基础上提出中国产业的集群式发展思路。     

Forecasting (aggregate) demand for US commercial air travel

We analyze whether it is better to forecast air travel demand using aggregate data at (say) a national level, or to aggregate the forecasts derived for individual airports using airport-specific data. We compare the US Federal Aviation Administration’s (FAA) practice of predicting the total number of passengers using macroeconomic variables with an equivalently specified AIM (aggregating individual markets) approach. The AIM approach outperforms the aggregate forecasting approach in terms of its out-of-sample air travel demand predictions for different forecast horizons. Variants of AIM, where we restrict the coefficient estimates of some explanatory variables to be the same across individual airports, generally dominate both the aggregate and AIM approaches. The superior out-of-sample performances of these so-called quasi-AIM approaches depend on the trade-off between heterogeneity and estimation uncertainty. We argue that the quasi-AIM approaches exploit the heterogeneity across individual airports efficiently, without suffering from as much estimation uncertainty as the AIM approach.