This paper presents the use of times series AutoRegressive Integrated Moving Average ARIMA(p,d,q) model with interventions, and neural network back-propagation model in analyzing the behavior of sales in a medium size enterprise located in Rio Grande do Sul Brazil for the period January 1984 – December 2000. The forecasts obtained using the neural network back-propagation model were found to be...

Recently Hybrid model approach has led to a tremendous surge in many domains of science and engineering. In this study, we present the advantage ANN improve time series forecasting precision. The Autoregressive Integrated Moving Average (ARIMA) Artificial Neural Network (ANN) models are used separately recognize linear nonlinear components data set respectively. manner, proposed tactically util...

Factors in the unit investment forecast of overhead line engineering are various and complex, it is very difficult to get the satisfied forecasting effect using traditional econometric models. In view of this characteristic, this thesis puts forward a kind of combination forecast model, using the ARIMA model and RBF neural network model to seek for linear and nonlinear change rule of historical...

Building a time series forecasting model by independent component analysis mechanism presents in the paper. Different from using the time series directly with the traditional ARIMA forecasting model, the underlying factors extracted from time series is the forecasting base in our model. Within component ambiguity, correlation approximation and mean difference problems, independent component ana...

Wind speed forecasting is difficult not only because of the influence of atmospheric dynamics but also for the impossibility of providing an accurate prediction with traditional statistical forecasting models that work by discovering an inner relationship within historical records. This paper develops a self-adaptive (SA) auto-regressive integrated moving average with exogenous variables (ARIMA...

With the increasing competition in the telecommunications industry, the operators try their best to increase telecom income via various measures, one of which is to set an amount of income as a goal to make the encouragement. Since accurate forecast of income plays an important role in income target setting, this paper builds a time series Autoregressive Integrated Moving Average Model (ARIMA) ...

By means of the Lee-Shrock transformation we generalize the 2D Gross-Neveu (GN2) model to a U(1) gauge theory with charged fermion and scalar fields in 2D (χUφ2 model). The χUφ2 model is equivalent to the GN2 model at infinite gauge coupling. We show that the dynamical fermion mass generation and asymptotic freedom in the effective four-fermion coupling persist also when the gauge coupling decr...

Statistical evidence suggests that the autocorrelation function (k) (k = 0; 1; : : :) of a compressed-video sequence is better captured by (k) = e ? p k than by (k) = k ? = e ? log k (long-range dependence) or (k) = e ?k (Markovian). A video model with such a correlation structure is introduced based on the so-called M jGj1 input processes. In essence, the M jGj1 process is a stationary version...

hydrological drought refers to a persistently low discharge and volume of water in streams and reservoirs, lasting months or years. hydrological drought is a natural phenomenon, but it may be exacerbated by human activities. hydrological droughts are usually related to meteorological droughts, and their recurrence interval varies accordingly. this study pursues to identify a stochastic model (o...

Based on an invariance-type property of the Lee-compositions of a linear Lee code, additional equality constraints can be introduced to the linear programming problem of linear Lee codes. In this paper, we formulate this property in terms of an action of the multiplicative group of the field [Formula: see text] on the set of Lee-compositions. We show some useful properties of certain sums of Le...