Partitions based computational method for high-order fuzzy time series forecasting
β Scribed by Sukhdev Singh Gangwar; Sanjay Kumar
- Book ID
- 116454158
- Publisher
- Elsevier Science
- Year
- 2012
- Tongue
- English
- Weight
- 305 KB
- Volume
- 39
- Category
- Article
- ISSN
- 0957-4174
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
Stock investors usually make their short-term investment decisions according to recent stock information such as the late market news, technical analysis reports, and price fluctuations. To reflect these short-term factors which impact stock price, this paper proposes a comprehensive fuzzy time-seri
## Abstract A new forecasting nonβGaussian time series method based on order series transformation properties has been proposed. The proposed method improves Yu's method without using Hermite polynomial expansion to process nonlinear instantaneous transformations and provides acceptable forecasting
In recent years, many researchers have presented different forecasting methods to deal with forecasting problems based on fuzzy time series. When we deal with forecasting problems using fuzzy time series, it is important to decide the length of each interval in the universe of discourse due to the f