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相关概念视频

Prediction Intervals01:03

Prediction Intervals

2.3K
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. 
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Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

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Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
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Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
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一种基于异质财务数据的结构化多头注意力预测方法.

Cheng Zhao1, Fangyong Li2, Zhe Peng3

  • 1Zhejiang University of Technology, School of Economics, Hangzhou, Zhejiang, China.

PeerJ. Computer science
|December 11, 2023
PubMed
概括
此摘要是机器生成的。

本研究引入了一种新的股票预测模型,使用定制数据处理和结构化的多头注意力机制来有效处理各种金融数据,提高预测准确度.

关键词:
不同质的财务数据股票预测 股票预测结构化的多头注意力.

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科学领域:

  • 分析财务数据 分析财务数据
  • 机器学习用于金融.
  • 股票市场预测 股票市场预测

背景情况:

  • 不同质的财务数据对准确的股票价格和交易量分析提出了挑战.
  • 有效处理各种数据类型对于稳健的财务预测模型至关重要.

研究的目的:

  • 提出一种新的股票预测模型,以解决异质金融数据的复杂性.
  • 通过定制的数据处理和注意力机制来增强特征提取和预测准确性.

主要方法:

  • 根据不同类型的财务数据特征量身定制的数据处理.
  • 结构化的多头注意力机制,单独分析技术,财务和情绪指标.
  • 模型评估使用中国A股市场四个代表性股票的实验数据.

主要成果:

  • 拟议的模型实现了1.378%的平均绝对百分比误差 (MAPE),比基准算法表现出色0.429%.
  • 后期测试显示,与基准相比,回报率的平均增长率为28.56%.
  • 通过对不同异质数据类型的个别关注来验证增强的预测准确性.

结论:

  • 定制的预处理方法显著改善了对异质金融数据的处理.
  • 结构化的多头关注机制有效地捕捉了各种金融指标对股价趋势的影响.
  • 拟议的模型为股票市场预测提供了更准确,更有利可图的方法.