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A Novel Machine Learning Strategy Based on Two-Dimensional Numerical Models in Financial Engineering
Author
Source
Mathematical Problems in Engineering
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-12-22
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Abstract EN
Machine learning is the most commonly used technique to address larger and more complex tasks by analyzing the most relevant information already present in databases.
In order to better predict the future trend of the index, this paper proposes a two-dimensional numerical model for machine learning to simulate major U.S.
stock market index and uses a nonlinear implicit finite-difference method to find numerical solutions of the two-dimensional simulation model.
The proposed machine learning method uses partial differential equations to predict the stock market and can be extensively used to accelerate large-scale data processing on the history database.
The experimental results show that the proposed algorithm reduces the prediction error and improves forecasting precision.
American Psychological Association (APA)
Xu, Qingzhen. 2013. A Novel Machine Learning Strategy Based on Two-Dimensional Numerical Models in Financial Engineering. Mathematical Problems in Engineering،Vol. 2013, no. 2013, pp.1-6.
https://search.emarefa.net/detail/BIM-1010278
Modern Language Association (MLA)
Xu, Qingzhen. A Novel Machine Learning Strategy Based on Two-Dimensional Numerical Models in Financial Engineering. Mathematical Problems in Engineering No. 2013 (2013), pp.1-6.
https://search.emarefa.net/detail/BIM-1010278
American Medical Association (AMA)
Xu, Qingzhen. A Novel Machine Learning Strategy Based on Two-Dimensional Numerical Models in Financial Engineering. Mathematical Problems in Engineering. 2013. Vol. 2013, no. 2013, pp.1-6.
https://search.emarefa.net/detail/BIM-1010278
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1010278