Research on Stock Prediction Model using Mode Decomposition Algorithm and Support Vector Regression-Reference-Cited by-同舟云学术

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Research on Stock Prediction Model using Mode Decomposition Algorithm and Support Vector Regression

Published:2024-01-19 Issue: Volume:17 Page:378-384
ISSN:
Container-title:Proceedings of the 2024 Guangdong-Hong Kong-Macao Greater Bay Area International Conference on Digital Economy and Artificial Intelligence
language:
Short-container-title:

Author:

Sun Yu¹^ORCID,Mutalib Sofianita²^ORCID,Omar ³^ORCID,Peng ⁴^ORCID

Affiliation:

1. Guangdong University of Science and Technology, China and Universiti Teknologi MARA, Malaysia

2. School of Computing Sciences, College of Computing, Informatics and Mathematics, Universiti Teknologi MARA, Malaysia

3. Universiti Teknologi MARA, Malaysia

4. Guangdong University of Science and Technology, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3675417.3675480

Reference15 articles.

1. Time series forecasting for nonlinear and non-stationary processes: a review and comparative study

2. Stock market prediction based on deep hybrid RNN model and sentiment analysis

3. Input dimension reduction for load forecasting based on support vector machines

4. Cherkassky V. & Ma Y. 2004. Practical selection of SVM parameters and noise estimation for SVM regression. Neural Networks 17(1)113-126.

5. A feature weighted support vector machine and K-nearest neighbor algorithm for stock market indices prediction

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