Forecast Methods for Time Series Data: A Survey

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

Some Forecast Methods in Regression Models for Categorical Time Series

We are dealing with the prediction of forthcoming outcomes of a categorical time series We will assume that the evolution of the time series is driven by a covariate process and by former outcomes and that the covariate process itself obeys an autoregressive law Two forecasting methods are presented The rst is based on an integral formula for the probabilities of forthcoming events and by a Mon...

a time-series analysis of the demand for life insurance in iran

با توجه به تجزیه و تحلیل داده ها ما دریافتیم که سطح درامد و تعداد نمایندگیها باتقاضای بیمه عمر رابطه مستقیم دارند و نرخ بهره و بار تکفل با تقاضای بیمه عمر رابطه عکس دارند

Time Series Abstraction Methods - A Survey

In knowledge discovery from time series the goal is to detect interesting patterns in the series that may help a human to better recognize the regularities in the observed variables and thereby improve the understanding of the system. Computer programs are very good in number crunching, but knowledge arises only in the head of a human. Ideally, knowledge discovery algorithms therefore use time ...

Tourism Time Series Forecast

In this chapter four combinations of input features and the feedforward, cascade forward and recurrent architectures are compared for the task of forecast tourism time series. The input features of the ANNs consist in the combination of the previous 12 months, the index time modeled by two nodes used to the year and month and one input with the daily hours of sunshine (insolation duration). The...