Inference and Forecasting for Fractional Autoregressive Integrated Moving Average Models, with an application to US and UK in ation

Inference and Forecasting for Fractional Autoregressive Integrated Moving Average Models, with an application to US and UK inflation

AN EXTENDED FUZZY ARTIFICIAL NEURAL NETWORKS MODEL FOR TIME SERIES FORECASTING

Improving time series forecastingaccuracy is an important yet often difficult task.Both theoretical and empirical findings haveindicated that integration of several models is an effectiveway to improve predictive performance, especiallywhen the models in combination are quite different. In this paper,a model of the hybrid artificial neural networks andfuzzy model is proposed for time series for...

Comparison of autoregressive integrated moving average (ARIMA) model and adaptive neuro-fuzzy inference system (ANFIS) model

Proper models for prediction of time series data can be an advantage in making important decisions. In this study, we tried with the comparison between one of the most useful classic models of economic evaluation, auto-regressive integrated moving average model and one of the most useful artificial intelligence models, adaptive neuro-fuzzy inference system (ANFIS), investigate modeling procedur...

Forecasting Gold Price Changes: Application of an Equipped Artificial Neural Network

The forecast of fluctuations and prices is the major concern in financial markets. Thus, developing an accurate and robust forecasting decision model is critically favorable to the investors. As gold has shown a special capability to smooth inflation fluctuations, governors use gold as a price controlling lever. Thus, more information about future gold price trends will help to make the firm de...

Application of a Statistical Model to Forecast Drowning Deaths in Iran

Background/aim:  One of the indicators for measuring the development of a country is its death rate caused by accidents and disasters. Every year, many people in Iran are drowned for various reasons. The aim of this study was to predict the trend of drowning mortality in Iran using statistical models. Method: This research was a longitudinal study using time-series data of drowning deaths obta...