Predicting daily occupancy is extremely important for the revenue management of individual hotels. However, daily occupancy can fluctuate widely and is difficult to forecast accurately based on existing forecasting methods. In this paper, Ensemble Empirical Mode Decomposition (EEMD)—a novel method—is introduced, and an individual hotel is chosen to test the effectiveness of EEMD in combination ...

We analyze the effects on prediction intervals of fitting ARIMA models to series with stochastic trends, when the underlying components are heteroscedastic. We show that ARIMA prediction intervals may be inadequate when only the transitory component is heteroscedastic. In this case, prediction intervals based on the unobserved component models tend to the homoscedastic intervals as the predicti...

Considering the time-series ARIMA(p,d, q) model and fuzzy regression model, this paper develops a fuzzy ARIMA (FARIMA) model and applies it to forecasting the exchange rate of NT dollars to US dollars. This model includes interval models with interval parameters and the possibility distribution of future values is provided by FARIMA. This model makes it possible for decision makers to forecast ...

زمینه و هدف: بیماری کبد چرب غیرالکلی رایج‌ترین کبدی است که در حال پیشرفت بوده بیش از یک‌چهارم مردم جهان را درگیر خود ساخته است. این پژوهشگران معتقدند فعالیت ورزشی استفاده داروهای گیاهی با خواص ضدچربی ضداکسایشی می‌تواند به‌عنوان درمان مکمل، سودمند باشد. بنابراین، هدف پژوهش تعیین آثار هشت هفته تمرین هوازی یا مصرف عرق آرتیشو بر سطوح چربی سرمی آنزیم‌های زنان مبتلا به بود. مواد روش‌ها: بدین‌منظور، 2...

In this paper an attempt is made to develop hybrid models using Artificial Neural Network (ANN) and Autoregressive Integrated Moving Average (ARIMA) for predicting the future exchange rate for US dollar. Simulation results of hybrid models were compared with results of ANN based models and ARIMA based models. Results show that the model ANN – ARIMA ANN gives a better performance than the other ...

Autoregressive integrated moving average (ARIMA) models are used in different researches for modelling and forecasting of traffic and Quality of Service (QoS) parameter values in telecommunication networks to make reasonable short, mediumand long-term predictions. We propose methodology to use ARIMA models for QoS prediction in network scenarios based on a preliminary detection and elimination ...