Modeling and forecasting the information sciences

Investigating the Effect of Non-financial Indicators on Forecasting the Occurrence of Financial Distress from the View of Urban Managers (Case Study: Bank Shahr)

The purpose of this study was to investigate the effect of non-financial indicators on forecasting The occurrence of financial distress in the Shahr Bank from the point of view of urban managers using the structural equation modeling approach. This research is an applied research in terms of purpose And in terms of method, it was a descriptive-survey study. The statistical population of the stu...

Modeling and forecasting US presidential election using learning algorithms

The primary objective of this research is to obtain an accurate forecasting model for the US presidential election. To identify a reliable model, artificial neural networks (ANN) and support vector regression (SVR) models are compared based on some specified performance measures. Moreover, six independent variables such as GDP, unemployment rate, the president’s approval rate, and others are co...

A Three-phase Hybrid Times Series Modeling Framework for Improved Hospital Inventory Demand Forecast

Background and Objectives: Efficient cost management in hospitals’ pharmaceutical inventories have the potential to remarkably contribute to optimization of overall hospital expenditures. To this end, reliable forecasting models for accurate prediction of future pharmaceutical demands are instrumental. While the linear methods are frequently used for forecasting purposes chiefly due to their si...

Tehran Stock Price Modeling and Forecasting Using Support Vector Regression (SVR) and Its Comparison with the Classic Model ARIMA

Flood Forecasting Using Artificial Neural Networks: an Application of Multi-Model Data Fusion technique

Floods are among the natural disasters that cause human hardship and economic loss. Establishing a viable flood forecasting and warning system for communities at risk can mitigate these adverse effects. However, establishing an accurate flood forecasting system is still challenging due to the lack of knowledge about the effective variables in forecasting. The present study has indicated that th...

Modeling and Forecasting Effects of Crude Oil Price Changes on the US and UK GDP

        This paper proposes a new forecasting model for investigating relationship between the price of crude oil, as an important energy source and GDP of the US, as the largest oil consumer, and the UK, as the oil producer. GMDH neural network and MLFF neural network approaches, which are both non-linear models, are employed to forecast GDP responses to the oil price changes. The resul...