Support Vector Machine and Granular Computing Based Time Series Volatility Prediction
With the development of information technology, a large amount of time-series data is generated and stored in the field of economic management, and the potential and valuable knowledge and information in the data can be mined to support management and decision-making activities by using data mining...
Saved in:
| Main Authors: | Yuan Yang, Xu Ma |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-01-01
|
| Series: | Journal of Robotics |
| Online Access: | http://dx.doi.org/10.1155/2022/4163992 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Some Granular Computing Based Machine Learning Algorithms
by: Vijay R. Tiwari
Published: (2025-06-01) -
Modeling and Predicting Time Series with Non-stationarity and Volatility
by: FENG Qiang, ZHAO Jianguang, YANG Rong, NIU Baoning
Published: (2025-05-01) -
Study on the effects of granularity of paprika on physicochemical properties and volatile flavor compounds of chili oil
by: YANG Fang, et al.
Published: (2023-12-01) -
Study on Prediction of Bearing Capacity of Compound Foundation with Support Vector Machine
by: ZHANG Wenjie, et al.
Published: (2010-01-01) -
SUPPORT VECTOR MACHINE METHOD FOR PREDICTING INVESTMENT MEASURES
by: Olga V. Kitova, et al.
Published: (2016-08-01)