ALGORITHM OF HYBRID GMDH-NETWORK CONSTRUCTION FOR TIME SERIES FORECAST

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

Sequential Network Construction for Time Series Prediction

This paper introduces an application of the Sequential Network Construction ( snc) method to select the size of several popular neural network predictor architectures for various benchmark training sets. The specific architectures considered are a fir network and the partially recurrent Elman network and its extension, with context units also added for the output layer. We consider an enhanceme...

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

A hybrid algorithm to forecast enrolment based on genetic algorithms and fuzzy time series

In this paper, we proposed a hybrid algorithm to forecast enrolment based on fuzzy time series and genetic algorithms, the proposed algorithms presents a good forecasting result with higher accuracy rate. Historical enrolment of the University of Alabama from year 1948 to 2010 are used in this study to illustrate the forecasting process.

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...