Time trajectories of medical costs-associated with onset of twelve aging-related cancer and chronic noncancer diseases were analyzed using the National Long-Term Care Survey data linked to Medicare Service Use files. A special procedure for selecting individuals with onset of each disease was developed and used for identification of the date at disease onset. Medical cost trajectories were foun...

Computational intelligence approaches have gradually established themselves as a popular tool for forecasting the complicated financial markets. Forecasting accuracy is one of the most important features of forecasting models; hence, never has research directed at improving upon the effectiveness of time series models stopped. Nowadays, despite the numerous time series forecasting models propos...

In airline industries, the aircraft maintenance cost takes up about 13% of the total operating cost. It can be reduced by a good planning. Spare parts inventories exist to serve the maintenance planning. Compared with commonly used reorder point system (ROP) and forecasting methods which only consider historical data, this paper presents two non-linear programming models which predict impending...

time series forecasting is an active research area that has drawn considerable attention for applications in a variety of areas. forecasting accuracy is one of the most important features of forecasting models. nowadays, despite the numerous time series forecasting models which have been proposed in several past decades, it is widely recognized that financial markets are extremely difficult to ...

 Cost-competitive with petroleum fuels  Long-term stable price for budget forecasting  Made from sustainable, renewable Biomass residuals  Storable and pumpable liquid similar to petroleum fuels  Clean burning fuel without the sulfur and particulates from petroleum fuels  Low greenhouse gas emissions Sustainability issues have become an important part of the supply chain for operati...

I n this paper, we specify that the GARCH(1,1) model has strong forecasting volatility and its usage under the truncated standard normal distribution (TSND) is more suitable than when it is under the normal and student-t distributions. On the contrary, no comparison was tried between the forecasting performance of volatility of the daily return series using the multi-step ahead forec...

In view of the characteristic that the traffic system is a dynamic and time-varying parameter system, the multi-level recursive forecasting method is proposed, and the multi-level recursive forecasting model of road accidents is established in this thesis. In this method, the forecasting of road accidents is divided into two parts: the forecasting of time-varying parameters and the future forec...

We evaluate several features of capacity planning approaches used in practice and make concrete suggestions for practitioners. We run four experiments to determine the eeects of large vs. small time buckets, the cost implications of using heuristics, frequent vs. less frequent forecasting and planning, and joint optimization of tool and oor-shell expansions vs. sequential optimization. We use i...