This paper gives the minimum generating sets of three types of one generator (1 + u)-quasi twisted (QT) codes over F 2 + uF 2 , u 2 = 0. Moreover, it discusses the generating sets and the lower bounds on the minimum Lee distance of a special class of A 2 type one generator (1 + u)-QT codes. Some good (optimal or suboptimal) linear codes over F 2 are obtained by these types of one generator (1 +...

the goal of this research is to predict total stock market index of tehran stock exchange, using the compound method of arima and neural network in order for the active participations of finance market as well as macro decision makers to be able to predict trend of the market. first, the series of price index was decomposed by wavelet transform, then the smooth's series  predicted by using...

Support Vector Regression (SVR) has been widely applied in time series forecasting. Considering long term predictions, iterative predictions perform many one-step-ahead predictions until the desired horizon is achieved. This process accumulates the error from previous predictions and may affect the quality of forecasts. In order to improve long term iterative predictions a hybrid multiple Autor...

The goal of this research is to predict total stock market index of Tehran Stock Exchange, using the compound method of ARIMA and neural network in order for the active participations of finance market as well as macro decision makers to be able to predict trend of the market. First, the series of price index was decomposed by wavelet transform, then the smooth's series  predicted by using...

0950-7051/$ see front matter 2010 Elsevier B.V. A doi:10.1016/j.knosys.2010.07.006 * Corresponding author. Tel.: +886 3 5712121x573 E-mail addresses: [email protected] (Y.-S (L.-I. Tong). The autoregressive integrated moving average (ARIMA), which is a conventional statistical method, is employed in many fields to construct models for forecasting time series. Although ARIMA can be adopte...

Soil moisture time series data are usually nonlinear in nature and influenced by multiple environmental factors. The traditional autoregressive integrated moving average (ARIMA) method has high prediction accuracy but is only suitable for linear problems predicts with a single column of series. gated recurrent unit neural network (GRU) can achieve the multivariate data, model does not yield opt...

In this work, the seasonality and performance loss rates of eleven grid-connected photovoltaic (PV) systems of different technologies were evaluated through seasonal adjustment. The classical seasonal decomposition (CSD) and X-12-ARIMA statistical techniques were applied on monthly DC performance ratio, RP, time series, constructed from field measurements over the systems' first five years of o...

5 This paper introduces Singular Spectrum Analysis (SSA) for tourism demand forecasting 6 via an application into total monthly U.S. Tourist arrivals from 1996-2012. The global 7 tourism industry is today, a key driver of foreign exchange inflows to an economy. Here, we 8 compare the forecasting results from SSA with those from ARIMA, Exponential Smoothing 9 (ETS) and Neural Networks (NN). We f...

The original definition of a stable model has been generalized to logic programs with aggregates. On the other hand, it was extended to first-order formulas using a syntactic transformation SM, similar to circumscription. In a recent paper, Lee and Meng combined these two ideas in a single framework by defining the operator SM for generalized formulas that may include, besides the usual syntact...

This paper discusses the prediction of inflation rate in Indonesia. The data used this research is assumed to have both linear and non-linear components. ARIMA model selected accommodate component, while ANFIS method accounts for component data. Thus, known as hybrid ARIMA-ANFIS model. clustering performed using Fuzzy C-Mean (FMS) with a Gaussian membership function. Consider 2 6 clusters. opti...