Abstract—The aim of this paper is to select the most accurate forecasting method for predicting the future values of the unemployment rate in selected European countries. In order to do so, several forecasting techniques adequate for forecasting time series with trend component, were selected, namely: double exponential smoothing (also known as Holt`s method) and Holt-Winters` method which acco...

Abstract—The aim of this paper is to select the most accurate forecasting method for predicting the future values of the unemployment rate in selected European countries. In order to do so, several forecasting techniques adequate for forecasting time series with trend component, were selected, namely: double exponential smoothing (also known as Holt`s method) and Holt-Winters` method which acco...

in the regulated nakdong river, algal proliferations are annually observed in some seasons, with cyanobacteria (microcystis aeruginosa) appearing in summer and diatom blooms (stephanodiscus hantzschii) in winter. this study aims to develop two ecological models forecasting future chlorophyll a at two time-steps (one-week and one-year forecasts), using recurrent neural networks tuned by genetic...

In recent years, some researchers used high-order fuzzy time series to deal with forecasting problems. In this paper, we present a new method for forecasting the enrollments of the University of Alabama based on the high-order fuzzy time series. The proposed method uses the socalled “second order differences” of the enrollments of the previous years to determine the trend of the forecasting. Th...

To counter strong features of disorder and randomness of stock market fluctuation in China, we introduce a Markov process model for the stock market trend forecasting, which is a useful complement for an existing technical analysis. Meanwhile, we expound on the related properties of Markov process and establish Markov chain mathematical model of the stock market trend forecasting, furthermore, ...

In this paper, we present a new approach to trend/cycle decomposition. The trend of an integrated time series is estimated using the conditional expectation of the steady-state level of the series. Given a nonlinear forecasting model, this steady-state approach can differ in important ways from the related long-horizon forecast decomposition proposed by Beveridge and Nelson (1981). We use gener...

Fuzzy time series model has been developed to either improve forecasting accuracy or reduce computation time, whereas a residul analysis in order to improve its forecasting performance is still lack of consideration. In this paper, we propose a novel Fourier method to revise the analysis of residual terms, and then we illustrate it to forecast the Japanese tourists visiting in Taiwan per year. ...