An improved combined small sample time series data prediction model
Pages 178 - 182
Abstract
Aiming at the problems that the current artificial intelligence (AI) large model can not accurately carry out small-sample time series data prediction and the sample incremental method was not applicable to small-sample time series data prediction, we proposed an improved combination prediction model for small-sample time series data. Firstly, we used multidimensional data incremental collection method based on the assumption of homogeneous distribution, incremental dataset slicing method, and parallel data preprocessing method to carry out incremental modeling for the sample set. Then, we carried out model selection and hyper-parameter optimization modeling, customized the selection method of optimal model and hyper-parameter combination and the definition of predictive data. Finally, the case study showed that the model proposed in this paper had higher prediction accuracy and broader applicability.
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Published In
December 2023
563 pages
ISBN:9798400708688
DOI:10.1145/3638584
Copyright © 2023 ACM.
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Association for Computing Machinery
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Published: 14 March 2024
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- Research-article
- Research
- Refereed limited
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- Chongqing Technology Innovation and Application Development Key Projects
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CSAI 2023
CSAI 2023: 2023 7th International Conference on Computer Science and Artificial Intelligence
December 8 - 10, 2023
Beijing, China
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