Tourism, one of the biggest industries in many countries, has been considered a complexly integrated and self-contained economic activity.As key determinants of thetourism demand are not fully identified to some extent different forecasting models vary in thelevel of accuracy. By comparing the performance of diverse forecasting models,including the linear regression, autoregressive integrated m...

BACKGROUND We previously proposed a hybrid model combining both the autoregressive integrated moving average (ARIMA) and the nonlinear autoregressive neural network (NARNN) models in forecasting schistosomiasis. Our purpose in the current study was to forecast the annual prevalence of human schistosomiasis in Yangxin County, using our ARIMA-NARNN model, thereby further certifying the reliabilit...

• Traditional approaches, including Box–Jenkins autoregressive integrated moving average (ARIMA) model, autoregressive and moving average with exogenous variables (ARMAX) model, seasonal autoregressive integrated moving average (SARIMA) model, exponential smoothing models [including Holt–Winters model (HW) and seasonal Holt and Winters’ linear exponential smoothing (SHW)], state space/Kalman fi...

OBJECTIVE Emergency department (ED) overcrowding is acknowledged as an increasingly important issue worldwide. Hospital managers are increasingly paying attention to ED crowding in order to provide higher quality medical services to patients. One of the crucial elements for a good management strategy is demand forecasting. Our study sought to construct an adequate model and to forecast monthly ...

neither damage mechanics model nor elastoplastic constitutive law can solely describe the behavior of concrete satisfactorily. in fact, they both fail to represent proper unloading slopes during cyclic loading. to overcome the disadvantages of pure plastic models and pure damage approaches, the combined effects need to be considered. in this regard, various classes of plastic-damage models have...

INTRODUCTION Box Jenkins’ linear autoregressive integrated moving average (ARIMA) methodology is widely used for analyzing time-series data. Beyond ‘linear’ domain, there are many nonlinear forms to be explored. In fact, nonlinear time-series analysis has been one of the major areas of research in Time-series analysis for more than two decades now. These models are generally more appropriate th...

â â â â â â â  this paper proposes a new forecasting model for investigating relationship between the price of crude oil, as an important energy source and gdp of the us, as the largest oil consumer, and the uk, as the oil producer. gmdh neural network and mlff neural network approaches, which are both non-linear models, are employed to forecast gdp responses to the oil price changes. the resul...

this paper attempts to compare the forecasting performance of the arima model and hybrid arma-garch models by using daily data of the iran’s exchange rate against the u.s. dollar (irr/usd) for the period of 20 march 2014 to 20 june 2015. the period of 20 march 2014 to 19 april 2015 was used to build the model while remaining data were used to do out of sample forecasting and check the forecasti...

Carlet 2] has determined the linear codes over Z=(4) of constant Lee weight. This extended abstract describes a diierent approach to this problem, along the lines of 4], which has the potential to apply to a wide class of examples. In particular, we show that linear codes of constant Lee or Euclidean weight seldom exist over Z=(p 2) when p is an odd prime. Over nite elds, any linear code with c...