| Issue |
ITM Web Conf.
Volume 77, 2025
2025 International Conference on Education, Management and Information Technology (EMIT 2025)
|
|
|---|---|---|
| Article Number | 01037 | |
| Number of page(s) | 5 | |
| DOI | https://doi.org/10.1051/itmconf/20257701037 | |
| Published online | 02 July 2025 | |
Construction and application of gold price prediction model based on historical data
Shandong Xiehe University, Jinan, Shandong, China, 250100
* Corresponding author: 653392026@qq.com
This article delves into the methods and practices of building gold price prediction models based on historical data. Predictive models were constructed using machine learning methods such as random forests and BP neural networks by collecting and preprocessing data on gold prices and related economic indicators from September 2022 to December 2023. Trained and validated, BP neural network models excel in prediction accuracy and stability due to their strong nonlinear fitting capabilities. It can provide investors with accurate decision-making basis and help to preserve and increase the value of assets.
Key words: Gold price prediction / Time series analysis / Machine learning / BP neural network
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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