Forecast Combinations of Computational Intelligence and Linear Models for the NN5 Time Series Forecasting competition
نویسندگان
چکیده
In this work we introduce a forecasting model with which we participated in the NN5 forecasting competition (the forecasting of 111 time series representing daily cash withdrawal amounts at ATM machines). The main idea of this ∗Accepted for publication in International Journal of Forecasting. Expected to appear in 2011.
منابع مشابه
A hybrid computational intelligence model for foreign exchange rate forecasting
Computational intelligence approaches have gradually established themselves as a popular tool for forecasting the complicated financial markets. Forecasting accuracy is one of the most important features of forecasting models; hence, never has research directed at improving upon the effectiveness of time series models stopped. Nowadays, despite the numerous time series forecasting models propos...
متن کاملA 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...
متن کاملForecasting Gold Price using Data Mining Techniques by Considering New Factors
Gold price forecast is of great importance. Many models were presented by researchers to forecast gold price. It seems that although different models could forecast gold price under different conditions, the new factors affecting gold price forecast have a significant importance and effect on the increase of forecast accuracy. In this paper, different factors were studied in comparison to the p...
متن کاملDay-ahead Price Forecasting of Electricity Markets by a New Hybrid Forecast Method
Energy price forecast is the key information for generating companies to prepare their bids in the electricity markets. However, this forecasting problem is complex due to nonlinear, non-stationary, and time variant behavior of electricity price time series. Accordingly, in this paper a new strategy is proposed for electricity price forecast. The forecast strategy includes Wavelet Transform (WT...
متن کاملAdaptive Fuzzy C-Regression Modeling for Time Series Forecasting
The aim of the 2015 IFSA-EUSFLAT International Time Series Competition, Computational Intelligence in Forecasting (CIF), is to evaluate the performance of computational intelligence-based approaches to forecast time series of different nature. The participants must propose a unique consistent methodology for all time series. This paper suggests an adaptive fuzzy c-regression modeling approach (...
متن کامل