کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
391151 661350 2008 18 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A new hybrid artificial neural networks and fuzzy regression model for time series forecasting
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
A new hybrid artificial neural networks and fuzzy regression model for time series forecasting
چکیده انگلیسی

Quantitative methods have nowadays become very important tools for forecasting purposes in financial markets as for improved decisions and investments. Forecasting accuracy is one of the most important factors involved in selecting a forecasting method; hence, never has research directed at improving upon the effectiveness of time series models stopped. Artificial neural networks (ANNs) are flexible computing frameworks and universal approximators that can be applied to a wide range of forecasting problems with a high degree of accuracy. However, ANNs need a large amount of historical data in order to yield accurate results. In a real world situation and in financial markets specifically, the environment is full of uncertainties and changes occur rapidly; thus, future situations must be usually forecasted using the scant data made available over a short span of time. Therefore, forecasting in these situations requires methods that work efficiently with incomplete data. Although fuzzy forecasting methods are suitable for incomplete data situations, their performance is not always satisfactory. In this paper, based on the basic concepts of ANNs and fuzzy regression models, a new hybrid method is proposed that yields more accurate results with incomplete data sets. In our proposed model, the advantages of ANNs and fuzzy regression are combined to overcome the limitations in both ANNs and fuzzy regression models. The empirical results of financial market forecasting indicate that the proposed model can be an effective way of improving forecasting accuracy.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Fuzzy Sets and Systems - Volume 159, Issue 7, 1 April 2008, Pages 769-786