一个新的混合间隔预测框架,集成多目标优化和量子深度学习,用于铜价预测

Yan Wang¹, Pei Du², Yan Xu^3,4

¹Ocean University of China, Qingdao, 266100, China.

Scientific reports

|October 21, 2025

概括

精确的铜价预测通过新的混合间隔预测框架得到了改进. 这种方法结合了量子深度学习和多目标优化,以获得更强大,更可靠的价格范围预测.

科学领域:

金融预测财务预测
计量经济学计量经济学
计算金融是一种计算金融.

背景情况:

准确的铜价预测至关重要,但由于市场波动而具有挑战性.
传统的单因素方法缺乏稳定性,无法考虑多种影响因素.

研究的目的:

为铜价预测开发一种新的混合间隔预测框架.
通过结合多个变量和先进的优化技术来提高预测准确性和稳定性.

主要方法:

开发了一个混合框架,将量子深度学习和多目标优化结合起来.
使用了四种概率预测算法和四种多目标优化算法.
使用特征选择方法来确定预测的关键变量.

主要成果:

量子回归长期短期记忆 (QRLSTM) 模型,通过多目标Salp Swarm算法 (MOSSA) 进行优化,表现出卓越的性能.
预测区间覆盖概率为94.5205%,预测区间正常化平均宽度为0.0066,可靠度为95%.
该模型的平均间隔得分为-373.9687,表明预测精度很高.

结论:

拟议的概率预测框架对于铜价预测是可靠和全面的.
混合方法有效地解决了单因素预测方法的局限性.
这项研究提供了一个可靠的解决方案,以应对金融市场波动的复杂性.

关键词:

深度学习是一种深度学习.多目标优化算法多目标优化算法概率预测可能预测.量子位回归是量子位回归的方法.

相关概念视频

01:03

Prediction Intervals

3.3K

The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.

3.3K

01:12

Quantitative Analysis

1.3K

Quantitative analysis is a technique for measuring the amount of specific constituents in a sample. When the sample's composition is unknown, qualitative analysis is performed first to identify its components, which ensures that the correct substances are measured during the quantitative phase.
In quantitative analysis, two key measurements are made: the sample quantity and a property proportional to the amount of the analyte (the substance being analyzed). This forms the basis of the...

1.3K

01:07

End Point Prediction: Gran Plot

1.1K

A Gran plot is used to predict the equivalence volume or endpoint of a potentiometric or acid-base titration without reaching the endpoint. Typically, titration data is collected as a function of the titrant's volume up to a point less than the equivalence volume and then transformed into a linear format. The straight line is extended to the x-axis, indicating the necessary titrant volume to achieve the equivalence point.
For potentiometric titration, the Gran plot is created by plotting...

1.1K

01:25

First Derivative Test: Problem Solving

Imagine an asset price that crashes to a low point, rebounds sharply as bargain-hunters step in, and then gradually declines. Such behavior can be modeled with a smooth function whose turning points represent locally overvalued and undervalued regions. A convenient example that captures rebound followed by decay is:The high and low points of this curve are identified using the first derivative test, which determines where the function changes from increasing to decreasing or vice versa. To...

02:52

Predicting Products: Substitution vs. Elimination

13.8K

When a nucleophile and an alkyl halide react, nucleophilic substitution and β-elimination reactions compete to generate products.
The following factors can influence the mechanisms competing against each other: