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相关概念视频

Prediction Intervals01:03

Prediction Intervals

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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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End Point Prediction: Gran Plot

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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.
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Expected Value01:15

Expected Value

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The expected value is known as the "long-term" average or mean. This means that over the long term of experimenting over and over, you would expect this average. The expected average is represented by the symbol μ. It is calculated as follows:
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Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
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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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Forces play a crucial role in the study of physics and engineering. They are essential in describing the motion, behavior, and equilibrium of objects in the physical world. Forces can be classified based on their origin, type, and direction of action.
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相关实验视频

Updated: Jun 14, 2025

Author Spotlight: IntelliSleepScorer — A High-Accuracy, Accessible GUI Software for Automated Sleep Stage Scoring in Mice and its Application in Psychiatric Research
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Author Spotlight: IntelliSleepScorer — A High-Accuracy, Accessible GUI Software for Automated Sleep Stage Scoring in Mice and its Application in Psychiatric Research

Published on: November 8, 2024

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基于可解释的深度学习模型的直播销售预测.

Lijun Wang1,2, Xian Zhang3

  • 1School of Software Engineering, University of Science and Technology of China, Hefei, 230026, China. kdchow@mail.ustc.edu.cn.

Scientific reports
|September 4, 2024
PubMed
概括

准确的销售预测对于直播电子商务至关重要. 新的深度学习模型SaleNet准确地预测销售量,具有高可解释性,满足业务需求.

关键词:
注意力机制注意力机制深度学习是一种深度学习.解释性分析可以解释.销售预测 销售预测

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科学领域:

  • 计算机科学 计算机科学
  • 业务分析 业务分析

背景情况:

  • 现场直播电子商务需要精确的销售量预测,以进行供需管理.
  • 准确的预测受到众多影响因素的挑战,需要强大和可解释的模型.

研究的目的:

  • 开发一种深度学习模型,用于在直播电子商务中准确和可解释的销售量预测.
  • 用现实世界的操作数据验证模型的性能.

主要方法:

  • 提出了SaleNet,这是一个针对销售量预测的新型深度学习架构.
  • 评估了SaleNet在私人实时电子商务数据上的预测准确性和可解释性.

主要成果:

  • 在+1.5天的预测中,实现了11.47%的低平均绝对百分比误差 (MAPE).
  • 实现了1周 (+6天) 预测的MAPE19.79%,与业务需求保持一致.
  • 证明了强大的模型解释性,功能贡献与现有研究和行业知识保持一致.

结论:

  • SaleNet提供了一个强大的,可解释的解决方案,用于在直播电子商务中预测销售量.
  • 这些发现为了解直播购物行为提供了理论基础.
  • 洞察力可以指导直播内容设计和用户体验优化.