Seepage forecast model based on time-series cubic exponential smoothing method

A Comparison Between Time Series, Exponential Smoothing, and Neural Network Methods To Forecast GDP of Iran

a comparison between time series, exponential smoothing, and neural network methods to forecast gdp of iran

A new adaptive exponential smoothing method for non-stationary time series with level shifts

Simple exponential smoothing (SES) methods are the most commonly used methods in forecasting and time series analysis. However, they are generally insensitive to non-stationary structural events such as level shifts, ramp shifts, and spikes or impulses. Similar to that of outliers in stationary time series, these non-stationary events will lead to increased level of errors in the forecasting pr...

Holt’s exponential smoothing model for interval-valued time series

Interval-valued time series are interval-valued data that are collected in a chronological sequence through time. This paper adapts an approach to forecasting interval valued-time series based on Holt’s exponential smoothing method. In the adapted Holt’s method for interval-valued time series, the smoothing parameters are estimated by using techniques for non-linear optimization problems with b...

Exponential smoothing for irregular time series

The paper deals with extensions of exponential smoothing type methods for univariate time series with irregular observations. An alternative method to Wright’s modification of simple exponential smoothing based on the corresponding ARIMA process is suggested. Exponential smoothing of order m for irregular data is derived. A similar method using a DLS (discounted least squares) estimation of pol...