کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
978729 | 933300 | 2006 | 11 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
The application of neural networks to forecast fuzzy time series
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
ریاضیات
فیزیک ریاضی
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: The application of neural networks to forecast fuzzy time series The application of neural networks to forecast fuzzy time series](/preview/png/978729.png)
چکیده انگلیسی
Fuzzy time series models have been applied to handle nonlinear problems. To forecast fuzzy time series, this study applies a backpropagation neural network because of its nonlinear structures. We propose two models: a basic model using a neural network approach to forecast all of the observations, and a hybrid model consisting of a neural network approach to forecast the known patterns as well as a simple method to forecast the unknown patterns. The stock index in Taiwan for the years 1991–2003 is chosen as the forecasting target. The empirical results show that the hybrid model outperforms both the basic and a conventional fuzzy time series models.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Physica A: Statistical Mechanics and its Applications - Volume 363, Issue 2, 1 May 2006, Pages 481–491
Journal: Physica A: Statistical Mechanics and its Applications - Volume 363, Issue 2, 1 May 2006, Pages 481–491
نویسندگان
Kunhuang Huarng, Tiffany Hui-Kuang Yu,