The value of feedback in forecasting competitions

In this paper we challenge the traditional design used for forecasting competitions. We implement an online competition with a public leaderboard that provides instant feedback to competitors who are allowed to revise and resubmit forecasts. The results show that feedback significantly improves forecasting accuracy.Forecasting competition, feedback.

Modelling and forecasting Australian domestic tourism

In this paper, we model and forecast Australian domestic tourism demand. We use a regression framework to estimate important economic relationships for domestic tourism demand. We also identify the impact of world events such as the 2000 Sydney Olympics and the 2002 Bali bombings on Australian domestic tourism. To explore the time series nature of the data, we use innovation state space models to forecast the domestic tourism demand. Combining these two frameworks, we build innovation state space models with exogenous variables. These models are able to capture the time series dynamics in the data, as well as economic and other relationships. We show that these models outperform alternative approaches for short-term forecasting and also produce sensible long-term forecasts. The forecasts are compared with the official Australian government forecasts, which are found to be more optimistic than our forecasts.Australia, domestic tourism, exponential smoothing, forecasting, innovation state space models.

STME Hydrogen Mixer Study

The hydrogen mixer for the Space Transportation Main Engine is used to mix cold hydrogen bypass flow with warm hydrogen coolant chamber gas, which is then fed to the injectors. It is very important to have a uniform fuel temperature at the injectors in order to minimize mixture ratio problems due to the fuel density variations. In addition, the fuel at the injector has certain total pressure requirements. In order to achieve these objectives, the hydrogen mixer must provide a thoroughly mixed fluid with a minimum pressure loss. The AEROVISC computational fluid dynamics (CFD) code was used to analyze the STME hydrogen mixer, and proved to be an effective tool in optimizing the mixer design. AEROVISC, which solves the Reynolds Stress-Averaged Navier-Stokes equations in primitive variable form, was used to assess the effectiveness of different mixer designs. Through a parametric study of mixer design variables, an optimal design was selected which minimized mixed fuel temperature variation and fuel mixer pressure loss. The use of CFD in the design process of the STME hydrogen mixer was effective in achieving an optimal mixer design while reducing the amount of hardware testing

A Comparison of Trout Streams: Examining the Reasons for Angler Visitation to Certain Counties Around North Carolina

Recreational fishing is a popular and profitable sport for states across the country (Ditton et al., 2002). Mountain trout angling provides as much as 174 million dollars annually to the state of North Carolina (NCWRC, 2009). This number shows that recreational trout fishing is an important economic factor for North Carolina. The goal of this project is to determine what variables correlate to the popularity of a county among trout anglers. Through personal experience, academic articles, and interviews with fly fishermen a list of variables was created in order to compare two streams in different counties. These variables include household median income, accessibility, proximity to fishing stores, and sex, age, and gender. The results show that some of these variables may in fact correlate to the popularity of a county among anglers in North Carolina. My findings may be helpful in the ability to predict the popularity of a trout stream when designating new trout water

Hierarchical forecasts for Australian domestic tourism

In this paper we explore the hierarchical nature of tourism demand time series and produce short-term forecasts for Australian domestic tourism. The data and forecasts are organized in a hierarchy based on disaggregating the data for different geographical regions and for different purposes of travel. We consider five approaches to hierarchical forecasting: two variations of the top-down approach, the bottom-up method, a newly proposed top-down approach where top-level forecasts are disaggregated according to forecasted proportions of lower level series, and a recently proposed optimal combination approach. Our forecast performance evaluation shows that the top-down approach based on forecast proportions and the optimal combination method perform best for the tourism hierarchies we consider. By applying these methods, we produce detailed forecasts for the Australian domestic tourism market.Australia, exponential smoothing, hierarchical forecasting, innovations state space models, optimal combination forecasts, top-down method, tourism demand.

Optimal combination forecasts for hierarchical time series

In many applications, there are multiple time series that are hierarchically organized and can be aggregated at several different levels in groups based on products, geography or some other features. We call these "hierarchical time series". They are commonly forecast using either a "bottom-up" or a "top-down" method. In this paper we propose a new approach to hierarchical forecasting which provides optimal forecasts that are better than forecasts produced by either a top-down or a bottom-up approach. Our method is based on independently forecasting all series at all levels of the hierarchy and then using a regression model to optimally combine and reconcile these forecasts. The resulting revised forecasts add up appropriately across the hierarchy, are unbiased and have minimum variance amongst all combination forecasts under some simple assumptions. We show in a simulation study that our method performs well compared to the top-down approach and the bottom-up method. It also allows us to construct prediction intervals for the resultant forecasts. Finally, we apply the method to forecasting Australian tourism demand where the data are disaggregated by purpose of visit and geographical region.Bottom-up forecasting, combining forecasts, GLS regression, hierarchical forecasting, Moore-Penrose inverse, reconciling forecasts, top-down forecasting.

Renal artery stenosis and hypertension : whom and how to screen and treat

Renovascular disease is an underlying cause in a significant proportion of patients who have refractory hypertension. Aggressive medical therapy to lower cardiovascular risk is the first priority in these patients. Endovascular treatment is required in only a few carefully selected cases<br /

Determining the focal length of a lens

There are many methods used to determine the focal length of a lens. This experimental method is based solely on the simplicity of the procedure

Clustered engine study

Several topics are presented in viewgraph form which together encompass the preliminary assessment of nuclear thermal rocket engine clustering. The study objectives, schedule, flow, and groundrules are covered. This is followed by the NASA groundrules mission and our interpretation of the associated operational scenario. The NASA reference vehicle is illustrated, then the four propulsion system options are examined. Each propulsion system's preliminary design, fluid systems, operating characteristics, thrust structure, dimensions, and mass properties are detailed as well as the associated key propulsion system/vehicle interfaces. A brief series of systems analysis is also covered including: thrust vector control requirements, engine out possibilities, propulsion system failure modes, surviving system requirements, and technology requirements. An assessment of vehicle/propulsion system impacts due to the lessons learned are presented