analyzing health series data and detecting anomalies: using forecasting methods to predict the next day's value, subtracting the … forecast to create residuals, and finally using detection algorithms on the residuals. The formalized framework indicates the … link between the forecast accuracy of the forecast method and the performance of the detector, and can be used to quantify …

Institute (CII) formed aresearch team to develop a new tool that can forecast the potential risk of not meetingspecific project …

Trueman [1994] provides a model of forecasting behavior in which analysts do not always make forecasts that are … sessions to investigate individual forecasting behavior. In each session, four individuals predict earnings based on possibly … divergent information. We manipulate forecast ability so that two individuals are strong analysts and two are weak. In three …

forecast when and how such behavioral changes will occur. These forecasting techniques, as well as any arbitrary time series …The ability to model, forecast, and analyze the behaviors of otheragents has applications in many diverse contexts. For … example, behavioral models can be used in multi-player games to forecast an opponent's next move, in economics to forecast a …

the present work is to simulate forecast of the monthly medium prices received by producers of melon in the State of Rio … arevages (ARIMA) thet better it is adjusted to he temporary series for forecast ends four models they are introduced candidates … for the accomplishment of the choice of the model of future forecast of the series. For your time, the choice of the best …

This study utilizes common time series forecasting methods to determine which of several simple, popular time series … forecasting techniques was the best predictor of the decline in United States weekly RevPAR as the lodging industry entered its … RevPAR data and utilized that data to test various moving average, exponential, and seasonal forecasting methods. The study …

The average hotel manager recognizes the criticality of forecasting. However, most managers are either frustrated by … theories. As hotel competition intensifies, managers require an effective method to forecast financial performance (Chon …, monthly and yearly (Wheaton & Rossof, 1998). This provides an opportunity for a time-series forecasting model for revenue …

, Euro zone and 4 EU countries and to identify the most appropriate forecasting ARIMA model for each time series. First, the … most appropriate ARIMA forecasting model of each time series are identified in the study. Practical investigation is … finalized with the comparison of PPI forecasting models of investigated countries. It has been identified that Austrian ARIMA …

Time series forecasting is an important area of forecasting in which past observations of the same variable are … explanatory variables. Time series can be modeled in a variety of ways e.g. using exponential smoothing techniques, regression … models, autoregressive (AR) techniques, moving averages (MA) etc. Recent research activities in forecasting also suggested …